• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.60-69
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• 1998

This paper proposes a speech synthesis method using Fuzzy VQ, and then study how to make choice of fuzziness value which optimizes (controls) the performance of FVQ in order to obtain the synthesized speech which is closer to the original speech. When FVQ is used to synthesize a speech, analysis stage generates membership function values which represents the degree to which an input speech pattern matches each speech patterns in codebook, and synthesis stage reproduces a synthesized speech, using membership function values which is obtained in analysis stage, fuzziness value, and fuzzy-c-means operation. By comparsion of the performance of the FVQ and VQ synthesizer with simmulation, we show that, although the FVQ codebook size is half of a VQ codebook size, the performance of FVQ is almost equal to that of VQ. This results imply that, when Fuzzy VQ is used to obtain the same performance with that of VQ in speech synthesis, we can reduce by half of memory size at a codebook storage. And then we have found that, for the optimized FVQ with maximum SQNR in synthesized speech, the fuzziness value should be small when the variance of analysis frame is relatively large, while fuzziness value should be large, when it is small. As a results of comparsion of the speeches synthesized by VQ and FVQ in their spectrogram of frequency domain, we have found that spectrum bands(formant frequency and pitch frequency) of FVQ synthesized speech are closer to the original speech than those using VQ.

• Journal of The Korean Society of Emergency Medicine
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• v.28 no.5
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• pp.457-466
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• 2017

Purpose: Traumatic brain injury (TBI) is a significant cause of morbidity and mortality worldwide. Severity of the initial insult is one of the most significant factors affecting outcome following TBI. In order to investigate the mechanisms of cellular injury and develop novel therapeutic strategies for TBI, we designed a standardized animal TBI model and evaluated histological and functional outcomes according to the degree of impact severity. Methods: Male adult C57Bl/6 mice underwent controlled cortical impact (CCI) at varying depths of deflection (1.0-2.0 mm). We performed hematoxylin and eosin staining at 7 days after recovery from TBI. Neurobehavioral characterization after TBI was analyzed by the Barnes maze test, passive avoidance test, open field test, rotarod test, tail suspension test, and light/dark test. Results: We observed a graded injury response according to the degree of deflection depths tested (diameter, 3 mm; velocity, 3 m/s; and duration, 500 ms) compared to sham controls. In the Barnes maze test, the severe TBI (2 mm depth) group showed reduced spatial memory as compared with the sham and mild TBI (1 mm depth) groups at 7 days after TBI. There was a significant difference in the results of the open field test and light/dark test among the three groups. Conclusion: Our findings demonstrate that the graded injury responses following TBI resulted in differential histopathological and behavioral outcomes in a mouse experimental CCI model. Thus, a model of CCI with histologic/behavioral outcome analysis may offer a reliable and convenient design for preclinical TBI research involving mice.

• Korean Journal of Comparative Education
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• v.24 no.5
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• pp.53-70
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• 2014

This study was performed in order to suggest the future model of Asian universities that could be used in the planning of the global competitive strategy. Futurologists forecasted the future of higher education using Harman Fan Scenario as like this. First, most current universities will be 'the satellite university' until 2015. Second, they also will replace 'the bookless university' until 2020. Third, they will be 'no calendar university' until 2025. And then they may be 'all have access university' until 2030. After 2030, futurologists prospected that almost universities based on off-line campus will be disappeared into the history. The analysis method of Harman fan scenario and applied scenarios were also used to "A study on the future scenario of Korean university". The predictive model and the alternative models were explored in a view point of students, enterprise, and government. Individuality with educational excellence are standardized for learner, profit and effectiveness are applied for enterpriser, and equality with welfare are adapted for national leader. Asian universities need to focus on bringing up the practical ability based on conscious and emotional education instead of knowledge based on memory. Also they need to enforce the specialized education that can create new jobs through convergence of interdisciplinary. Especially, Asian nations need to explore, to find the strengthen area of their universities compared with USA. And these area should be specialized. The convergency strategy between oriental medicine and informatics is a meaningful sample. Based on this point, a predicted with 3 alternative scenarios in a view point of equality were suggested for the future of Asian universities.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.875-888
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• 2021

In this paper, we search integral distinguishers of lightweight block cipher PIPO and propose a key recovery attack on 8-round PIPO-64/128 with the obtained 6-round distinguishers. The lightweight block cipher PIPO proposed in ICISC 2020 is designed to provide the efficient implementation of high-order masking for side-channel attack resistance. In the proposal, various attacks such as differential and linear cryptanalyses were applied to show the sufficient security strength. However, the designers leave integral attack to be conducted and only show that it is unlikely for PIPO to have integral distinguishers longer than 5-round PIPO without further analysis on Division Property. In this paper, we search integral distinguishers of PIPO using a MILP-aided Division Property search method. Our search can show that there exist 6-round integral distinguishers, which is different from what the designers insist. We also consider linear operation on input and output of distinguisher, respectively, and manage to obtain totally 136 6-round integral distinguishers. Finally, we present an 8-round PIPO-64/128 key recovery attack with time complexity 2^124.5849 and memory complexity of 2⁹³ with four 6-round integral distinguishers among the entire obtained distinguishers.

• (The) Research of the performance art and culture
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• no.36
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• pp.365-414
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• 2018

This paper studied the type and character of the Divinity in Korean shamanism. The study of the Divinity means the hierarchy of shamanism, the relationship between shamanism and divinity, and the comparison between shamanism and divinity. The study of the shamanistic divinity based on Kim Tae - Gon's collection of anthology by Shaman(1971). The Jaesugut was composed of the contents of the gods blessing human beings. The JaesuGut of Seoul vary from 10 to 18 depending on the author. The JaesuGut of Goseong consists of 8 Gut. The essence of the ritual gut is to pray for the peace of the individual by using the world which is not explained by reason and science. It is a reincarnation that reflects the world of experience that is stored in the memory of human being that both reason and science can not explain. And the desire to escape from fear was reflected in Jaesu Gut. Every Jaesu Gut in Seoul and Goseong has a main divinity. This main divinity is attached to the divinity in another Gut and becomes a subordination divinity. It also becomes a subordinate-subordination divinity to the another Gut. The gods of reincarnation are basically taken in the order of national security ${\rightarrow}$ local security ${\rightarrow}$ home security.

• The Korean Journal of Archival Studies
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• no.10
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• pp.145-194
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• 2004

Church archives are the evidential instruments to remember church activity and important information aggregate which has administrative, legal, financial, historical, faithful value as the collective memory of church community. So it must be managed necessarily and the management orders are based on the Bible. The western churches which have a correct understanding about the importance of church records and management order have taken multilateral endeavor to create, manage church archives systematically. On the other hand, korean churches don't have the records management systems. Therefore, Records created in individual church are mostly managed unsystematically and exist as 'backlogs', finally, they are destructed without reasonable formalities. In those problems, the purpose of this study is to offer the way of records classification and disposition instrument with recognition that records management should be done from the time of creation or previous to it. As a concrete device for them, I tried to embody the function-based classification method and disposal schedule. I prefer the function-based classification and disposal schedule to the organization and function-based classification to present stable classification and disposal schedule, as we can say the best feature of the modern organization is multilateral and also churches have same aspect. For this study, I applied DIRKS(Designing and Implementing Recordkeeping Systems) manual which National Archives of Australia provide and guidelines in ICA/IRMT series to construct the theory of the function-based classification in individual churches. Through them, it was possible to present a model for preliminary investigation, analysis of business activity, records survey, disposal schedule. And I took an example of 'Myong Sung Presbyterian Church' which belong to 'The Presbyterian church in Korea'. I explained in detail codifying process and results of preliminary investigation in 'Myong Sung Presbyterian Church', analysis of business activity based on it, process of presenting the function-based classification and disposal schedule got from all those steps. For establishing disposal schedule, I planned 'General Disposal Schedule' and 'Agency Disposal Schedule' which categorized 'general function' and 'agency function' of an agency, according to DIRKS in Australia and ICA/IRMT. And for estimation of disposal date I had a thorough grasp of important records category presented in 'Constitution of General Assembly', interview to know the importance of tasks, and added examples of disposal schedule in western church archives. This study has significance that it was intended to embody 'the function-based classification' and 'disposal schedule' suitable for individual church, applying DIRKS in Australia and ICA/IRMT on absence of the theory or example which tried to present the function-based classification and disposal schedule for individual church. Also it is meaningful to present a model that can classify and disposal real records according to the function in individual church which has no recognition or way about records management.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.373-382
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• 2019

This study was performed to investigate the effects of creative teaching technique(CTT) on critical thinking disposition(CTD), problem solving process(PSP), and self-leadership(SL) in 5 majors of first to third grades in a college nursing department. CTT was developed to promote memory and practical ability. The study was conducted from August 1 to December 31 in 2017, and the survey was performed before and after applying the CTT. As a result, there was no difference in CTD, PSP, and SL in the first graders whom applied various teaching techniques to one subject. But CTD was 6.8point(p<0.001), PSP was 7.5~7.9point(p<0.001) and SL was 2.9~3.3point(p<0.001) improved in the second and third grades whom applied similar teaching techniques in two subjects. In order to improve the students' core competency, it is more effective for students to apply one or two methods repeatedly in several subjects than to apply various methods to one subject. Since the CTT was more effective in the group that selected the major depending on aptitude and interest, it is necessary to develop various teaching and learning strategies to enhance the interest in nursing major.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.310-318
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• 2018

Recently, the importance of big data analysis is increasing as a large amount of data is generated by various devices connected to the Internet with the advent of Internet of Things (IoT). Especially, it is necessary to analyze various large-scale IoT streaming sensor data generated in real time and provide various services through new meaningful prediction. This paper proposes a real-time indoor PM10 concentration prediction LSTM model based on streaming data generated from IoT sensor using AWS. We also construct a real-time indoor PM10 concentration prediction service based on the proposed model. Data used in the paper is streaming data collected from the PM10 IoT sensor for 24 hours. This time series data is converted into sequence data consisting of 30 consecutive values from time series data for use as input data of LSTM. The LSTM model is learned through a sliding window process of moving to the immediately adjacent dataset. In order to improve the performance of the model, incremental learning method is applied to the streaming data collected every 24 hours. The linear regression and recurrent neural networks (RNN) models are compared to evaluate the performance of LSTM model. Experimental results show that the proposed LSTM prediction model has 700% improvement over linear regression and 140% improvement over RNN model for its performance level.

• Journal of IKEEE
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• v.22 no.4
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• pp.1214-1217
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• 2018

In this paper, we propose the development of a Small $360^{\circ}$ Oral Scanner embedded board. The proposed small $360^{\circ}$ oral scanner embedded board consists of image level and transfer method changing part FPGA part, memory part and FIFO to USB transfer part. The image level and transmission mode change unit divides the MIPI format oral image received through the small $360^{\circ}$ oral cavity image sensor and the image sensor into low power signal mode and high speed signal mode and distributes them to the port and transfers the level shift to the FPGA unit. The FPGA unit performs functions such as $360^{\circ}$ image distortion correction, image correction, image processing, and image compression. In the FIFO to USB transfer section, the RAW data transferred through the FIFO in the FPGA is transferred to the PC using USB 3.0, USB 3.1, etc. using the transceiver chip. In order to evaluate the efficiency of the proposed small $360^{\circ}$ oral scanner embedded board, it has been tested by an authorized testing institute. As a result, the frame rate per second is over 60 fps and the data transfer rate is 4.99 Gb/second

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.301-309
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• 2021

In this study, we tried to improve the performance of the existing U-net-based deep learning rainfall prediction model, which can weaken the meaning of time series order. For this, ConvLSTM2D U-Net structure model considering temporal consistency of data was applied, and we evaluated accuracy of the ConvLSTM2D U-Net model using a RainNet model and an extrapolation-based advection model. In addition, we tried to improve the uncertainty in the model training process by performing learning not only with a single model but also with 10 ensemble models. The trained neural network rainfall prediction model was optimized to generate 10-minute advance prediction data using four consecutive data of the past 30 minutes from the present. The results of deep learning rainfall prediction models are difficult to identify schematically distinct differences, but with ConvLSTM2D U-Net, the magnitude of the prediction error is the smallest and the location of rainfall is relatively accurate. In particular, the ensemble ConvLSTM2D U-Net showed high CSI, low MAE, and a narrow error range, and predicted rainfall more accurately and stable prediction performance than other models. However, the prediction performance for a specific point was very low compared to the prediction performance for the entire area, and the deep learning rainfall prediction model also had limitations. Through this study, it was confirmed that the ConvLSTM2D U-Net neural network structure to account for the change of time could increase the prediction accuracy, but there is still a limitation of the convolution deep neural network model due to spatial smoothing in the strong rainfall region or detailed rainfall prediction.