• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.100-106
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• 2021

Over the past few decades, natural language processing research has not made much. However, the widespread use of deep learning and neural networks attracted attention for the application of neural networks in natural language processing. Sentiment analysis is one of the challenges of natural language processing. Emotions are things that a person thinks and feels. Therefore, sentiment analysis should be able to analyze the person's attitude, opinions, and inclinations in text or actual text. In the case of emotion analysis, it is a priority to simply classify two emotions: positive and negative. In this paper we propose the deep learning based sentimental analysis system according to various optimizer that is SGD, ADAM and RMSProp. Through experimental result RMSprop optimizer shows the best performance compared to others on IMDB data set. Future work is to find more best hyper parameter for sentimental analysis system.

• KCI Concrete Journal
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• v.12 no.2
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• pp.3-10
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• 2000

A computer program, named NEO-PCBRG, for the analysis and design of prestressed con-crete(PSC) bridges was developed using the finite element method. NEO-PCBRG can predict the response of PSC bridges throughout the various stages of construction and service. NEO-PCBRG has both pre- and post-processing capabilities. Pre-processing refers to all the neces- sary steps required to prepare a virtual prototype, more commonly termed a varied model for analysis. Post-processing here stands for the step in which the results from the analysis are reviewed and interpreted. In order to allow for the easy and convenient execution of the entire procedure, NEO-PCBRG was developed using computer graphics in the Visual Basic pro- gramming language. In conclusion, this study presents a new software architecture for analy-sis using the user-oriented design technique.

• Journal of the Korean Society of Visualization
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• v.13 no.3
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• pp.15-19
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• 2015

We developed a high-throughput microscopy (HTM) method which enabled us to replace a conventional phase contrast microscopy (PCM) method that has been used as a standard analytical method for airborne asbestos. We could obtain the concentration of airborne asbestos fibers under detection limit by automated image processing and analysis using HTM method. Here we propose an improved image processing algorithm with variable parameters to enhance the accuracy of the HTM analysis. Since the variable parameters that compensate the difference of the brightness are applied to the individual images in our new image processing method, it is possible to enhance the accuracy of the automatic image analysis method for sample slides with low asbestos concentration that caused errors in binary image processing. We demonstrated that enumeration of fibers by improved image processing algorithm remarkably enhanced the accuracy of HTM analysis in comparison with PCM. The improved HTM method can be a potential alternative to conventional PCM.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.403-417
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• 2016

This paper reviews recent published works dealing with the application of wavelets to image processing based on multiresolution analysis. After revisiting the basics of wavelet transform theory, various applications of wavelets and multiresolution analysis are reviewed, including image denoising, image enhancement, super-resolution, and image compression. In addition, we introduce the concept and theory of quaternion wavelets for the future advancement of wavelet transform and quaternion multiresolution applications.

• Journal of Wind Energy
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• v.4 no.1
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• pp.20-29
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• 2013

Load measurement, which is performed based on IEC 61400-13, consists of three stages: the stage of collecting huge amounts of load measurement data through a measurement campaign lasting for several months; the stage of processing the measured data, including data validation and classification; and the stage of analyzing the processed data through time series analysis, load statistics analysis, frequency analysis, load spectrum analysis, and equivalent load analysis. In this research, we pursued the development of an analysis software in MATLAB to save labor and to secure exact and consistent performance evaluation data in processing and analyzing load measurement data. The completed analysis software also includes the functions of processing and analyzing power performance measurement data in accordance with IEC 61400-12. The analysis software was effectively applied to process and analyse the load measurement data from a demonstration research for a 750 kW direct-drive wind turbine generator system (KBP-750D), performed at the Daegwanryeong Wind Turbine Demonstration Complex. This paper describes the details of the analysis software and its processing and analysis stages for load measurement data and presents the analysis results.

• 한국전자현미경학회:학술대회논문집
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• 1995.06a
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• pp.48-49
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• 1995

• Journal of KIISE
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• v.45 no.2
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• pp.99-105
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• 2018

One of the spatial statistical analysis, hotspot analysis is one of easy method of see spatial patterns. It is based on the concept that "Adjacent ones are more relevant than those that are far away". However, in hotspot analysis is spatial adjacency must be considered, Therefore, distributed processing is not easy. In this paper, we proposed a distributed algorithm design for hotspot spatial analysis. Its performance was compared to standalone system and Hadoop, Spark based processing. As a result, it is compare to standalone system, Performance improvement rate of Hadoop at 625.89% and Spark at 870.14%. Furthermore, performance improvement rate is high at Spark processing than Hadoop at as more large data set.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.9_10 s.146
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• pp.1329-1339
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• 2005

The purpose of this study was to investigate the effect of consumer knowledge and involvement of apparel products on information processing style. The subjects of this study were female adults who lived in Seoul, Kyunggi or Incheon areas and Quota sampling using age and residential areas was employed. The data were obtained from 603 questionnaires. Data were statistically analyzed using SPSS 10 and LISREL 7.0. Major statistical methods were factor analysis, Cronbach's a coefficient, multiple regression analysis, and structural equation model analysis. The results were as follows: 1. Consumer knowledge significantly influenced information processing styles. Rational processing style was significantly influenced by objective knowledge, while experiential processing style was significantly influenced by subjective knowledge. 2. Involvement was related to the subjective knowledge more than objective knowledge. Consumers who had higher interest, social importance and followed latest fashion trends tended to process information more experientially.

• The Journal of Fisheries Business Administration
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• v.52 no.4
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• pp.45-63
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• 2021

The purpose of this study is to analyze the structure, status and economic ripple effects of the fisheries processing industry in Korea using interindustry analysis. Five input-output tables published over the past twenty years have been reclassified with a focus on the fisheries processing sector. Through these multi-period tables, we analyzed changes in the inducing effects in production, value added and employment as well as the backward-forward linkage effects. As a result of the analysis, it was found that the industrial scale of the fisheries processing industry is very small compared to other food manufacturing industries. The backward linkage effect of the fisheries processing industry was greater than that of other industries, but the forward linkage effect was rather low. This means that the fisheries processing industry can be greatly affected by industrial depression of the downstream industries such as fishery and aquaculture. Production and employment-inducing effects of the fisheries processing industry have shown a decreasing trend in recent years. This reflects the reality that intermediate inputs are gradually being replaced by imports from domestic production due to the expansion of market opening and the depletion of fishery resource. In the future, it is necessary to prepare a strategy to increase the value-added productivity of the fisheries processing sector and foster it as an export industry.

• Journal of Korea Entertainment Industry Association
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• v.13 no.3
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• pp.203-211
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• 2019

The purpose of this study was to investigate the relations between sensory processing and sleep disturbances and to investigate the effect of sensory processing on sleep disorder in preschool children with developmental disorder. This study was conducted for 110 children with developmental disorder in developmental clinic and rehabilitation hospital in Gwang Ju from June to August, 2017. The final 109 data were analyzed. Sensory processing and Sleep disturbances were measured using the Shortened sensory profile(SSP) and Korean-the Children's Sleep Habits Questionnaire(K-CSHQ). Statistical analysis was performed using descriptive analysis, Pearson correlation analysis, and multiple regression analysis were performed. Children with developmental disorder had problems with sensory processing and sleep habits. Sensory processing was related to sleep habit and most important factors of sensory processing influencing sleep was taste/olfactory sensitivity, auditory filtering. Conclusion: In order to help children with developmental disorder with sleep problem, it is necessary to consider the sensory processing especially taste/olfactory sensitivity, auditory filtering.