• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.190-198
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• 2023

Sentiment analysis can be applied to all texts generated from websites, blogs, messengers, etc. The study fulfills an artificial intelligence sentiment analysis estimating visiting evaluation opinions (reviews) and visitor ratings, and suggests a deep learning model which foretells either an affirmative or a negative inclination for new reviews. This study operates review big data about Jeju tourist attractions which are extracted from Google from October 1st, 2021 to November 30th, 2021. The normalization data used in the propensity prediction modeling of this study were divided into training data and test data at a 7.5:2.5 ratio, and the CNN classification neural network was used for learning. The predictive model of the research indicates an accuracy of approximately 84.72%, which shows that it can upgrade performance in the future as evaluating its error rate and learning precision.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.911-921
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• 2017

The purpose of this study was to investigate the semantic network analysis to understand image contents and to examine the degree to which words, word clusters contributed to the formation of semantic map within image contents. For this research, from 1993 until 2016 the field of the image contents were collected for a total of 2,624 cases papers. The word appeared in Title analyzed the social network by using the R program of Big Data. The results were as follows: First, Research on 'education' in the field of image contents has decreased. Second, the role of 'media' in the field of image contents is changing. Finally, It is a change in the status of 'contents' in the field of image contents.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.81-89
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• 2022

This study aims to analyze the images of Instagram posts and to draw implcations regarding the exhibition of . This study collects and crawl 24,295 images from Instagram posts as a dataset. We use the Google Cloud Vision API for labeling the images and a total of 212,567 clusters of labels are finally classified into 9 categories using Word2Vec. The categories of museum spaces, photo zone, architecture category are dominant along with people category. In conclusion, visitors curate their experiences and memories of physical places and spaces while they are experiencing with the exhibition. This result reproves the results of previous studies which emphasize a sense of social presence and place making. The convergent approach of art management and art technology used in this study help museum professionals have an insight on big data based visitor research on a practical level.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.9
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• pp.27-35
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• 2016

Today, with the advance of Information and communication technology, 'Smart, connected' toys, which apply technologies related to IoT (Internet of Things) to traditional toys, are emerging and rapidly growing. This research aims to analyze the tendencies and limitations of smart, connected toys through exploring the representative cases of smart, connected toys based on characteristics of ICBM (Internet of Things, Cloud, Big-data, and Mobile) technology. For this study, we begin by understanding literature research about smart, connected toys and ICBM technology. Then, we extracted the characteristics of ICBM technology for connecting physical and digital environments through investigating cases to which ICBM technologies are applied. Based on the extracted characteristics, the case studies of smart, connected toys were conducted. In this research, we explore the level of ICBM technology application and limitation to smart, connected toys. We expect this research will contribute to providing guidelines for developing smart, connected toys based on the characteristics of the latest technology.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.196-204
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• 2017

Behavior of intelligent video surveillance system is recognized by analyzing the pattern of the object of interest by using the frame information of video inputted from the camera and analyzes the behavior. Detection of object's certain behaviors in the crowd has become a critical problem because in the event of terror strikes. Recognition of object's certain behaviors is an important but difficult problem in the area of computer vision. As the realization of big data utilizing machine learning, data mining techniques, the amount of video through the CCTV, Smart-phone and Drone's video has increased dramatically. In this paper, we propose a multiple-sliding window method to recognize the cumulative change as one piece in order to improve the accuracy of the recognition. The experimental results demonstrated the method was robust and efficient learning units in the classification of certain behaviors.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.1
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• pp.387-394
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• 2019

Recently, the importance of big data has been increased, and demand for data analysis for the big data is also increased. R language is developed for data analysis, and users are analyzing data by using algorithms of various statistics, machine learning and data mining packages in R language. However, it is difficult to develop an application using R. Early study proposed a method to call R script through another language such as PHP, Java, and so on. However, it is troublesome to write such a development method in addition to R in combination with other languages. In this study, we introduce how to write API using only R language without using another language by using Plumber package. We also propose a solution for security issues related with R API. If we use propose technology for developing web application, we can expect high productivity, easy of use, and easy of maintenance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.769-786
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• 2016

Object recognition and object location have always drawn much interest. Also, recently various computational models have been designed. One of the big issues in this domain is the lack of an appropriate model for extracting important part of the picture and estimating the object place in the same environments that caused low accuracy. To solve this problem, a new Salient Based Bag of Visual Word (SBBoVW) model for object recognition and object location estimation is presented. Contributions lied in the present study are two-fold. One is to introduce a new approach, which is a Salient Based Bag of Visual Word model (SBBoVW) to recognize difficult objects that have had low accuracy in previous methods. This method integrates SIFT features of the original and salient parts of pictures and fuses them together to generate better codebooks using bag of visual word method. The second contribution is to introduce a new algorithm for finding object place based on the salient map automatically. The performance evaluation on several data sets proves that the new approach outperforms other state-of-the-arts.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.27-33
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• 2009

The emergences of GeoSensor and researches about GIS have promoted many researches of u-GIS. The disaster application coupled in the u-GIS can apply to monitor accident area and to prevent spread of accident. The application needs the u-GIS DSMS technique to acquire, to process GeoSensor data and to integrate them with GIS data. The u-GIS DSMS must process big and large-volume data stream such as spatial data and multimedia data. Due to the feature of the data stream, in u-GIS DSMS, query processing can be delayed. Moreover, as increasing the input rate of data in the area generating events, the network traffic is increased. To solve this problem, in this paper we describe TRIGGER ACTION clause in CQ on the u-GIS DSMS environment and proposes data source management. Data source weight table controls GES information and incoming data rate. It controls incoming data rate as increasing weight at GES of disaster area. Consequently, it can contribute query processing rate and accuracy

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1817-1823
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• 2011

OFDM Modulation is used for multimedia transmission At Urban Train. Recently the application field about data transmission is expanding the image as well. The case which the number of OFDM carrier is big is advantageous because multipass fading is big 18GHz wireless frequency. Existing WLAN which an ethernet transmission is possible is not suitable to a great distance transmission because number of carrier is 64. In this paper, we developed OFDM modem suitable to transmit broadband data at high speed train. A doppler compensation block added to offset the doppler effect. Therefore, the effectiveness is expected to be very big in field of urban train.

• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1219-1224
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• 2018

Nowaday, smart mobile devices on Internet of Things are required to process and deliver greate amount of data in real-time. Therefore, heterogeneous mult-core architecture such the big.LITTLE core architecture, which shows high energy conservation while guaranteeing high performance, are widely employed on up to date smart mobile devices. The LITTLE cores should be highly utilized to gain higher energy conservation because LITTLE cores have much higher energy efficiency than big cores. In this paper, we propose a core selection algorithm, which tries to firstly assign a real-time task on a LITTLE core rather a big core while the task can be finished within its own deadline. We also perform simulation as performance evaluation to show that our proposed algorithm shows higher energy conservation while guaranteeing the required performance.