• Proceedings of the KSPS conference
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• 2007.05a
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• pp.91-94
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• 2007

This paper aims to analyze the pronunciation of Korean Point-of-Interest (POI) data, which consist of 224 sound files, from the phonological point of view, adapting the notion of prosodic word within the framework of Intonational Phonology. Each POI word is broken down into prosodic words, which are defined as the minimal sequence of segments which can be produced as one Accentual Phrase (AP). Then the pronunciation of the POI word considering its prosodic words are analyzed. The results show that: in most cases, a prosodic word is realized as one AP; that, in some cases, two prosodic words are pronounced as one AP: and that no cases are found where 3 prosodic words are realized as one AP.

• Journal of the Semiconductor & Display Technology
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• v.17 no.4
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• pp.21-26
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• 2018

Recently, the emergence of 3D cameras, 3D scanners and various cameras including Lidar is expected to be applied to applications such as AR, VR, and autonomous mobile vehicles that deal with 3D data. In Particular, the 3D point cloud data consisting of tens to hundreds of thousands of 3D points is rapidly increased in capacity compared with 2D data, Efficient encoding / decoding technology for smooth service within a limited bandwidth, and efficient service provision technology for differentiating the area of interest and the surrounding area are needed. In this paper, we propose a new quality parameter considering characteristics of 3D point cloud instead of quality change based on assumed video codec in MPEG V-PCC used in 3D point cloud compression, 3D Grid division method and representation for selectively transmitting 3D point clouds according to user's area of interest, and propose a new 3D Manifesto. By using the proposed technique, it is possible to generate more bitrate images, and it is confirmed that the efficiency of network, decoder, and renderer can be increased while selectively transmitting as needed.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.528-537
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• 2015

Text in images is one of the most important cues for understanding a scene. In this paper, we propose a novel approach based on interest points to localize text in natural scene images. The main ideas of this approach are as follows: first we used interest point detection techniques, which extract the corner points of characters and center points of edge connected components, to select candidate regions. Second, these candidate regions were verified by using tensor voting, which is capable of extracting perceptual structures from noisy data. Finally, area, orientation, and aspect ratio were used to filter out non-text regions. The proposed method was tested on the ICDAR 2003 dataset and images of wine labels. The experiment results show the validity of this approach.

• MALSORI
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• no.57
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• pp.123-137
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• 2006

This paper aims to propose a method of detecting irregular pronunciations for Korean POI data adopting the notion of the Prosodic Word based on the Prosodic Phonology (Selkirk 1984, Nespor and Vogel 1986) and Intonational Phonology (Jun 1996). In order to show the performance of the proposed method, the detection experiment was conducted on the 250,000 POI data. When all the data were trained, 99.99% of the exceptional prosodic words were detected, which shows the stability of the system. The results show that similar ratio of exceptional prosodic words (22.4% on average) were detected on each stage where a certain amount of the training data were added. Being intended to be an example of an interdisciplinary study of linguistics and computer science, this study will, on the one hand, provide an understanding of Korean language from the phonological point of view, and, on the other hand, enable a systematic development of a multiple pronunciation lexicon for Korean TTS or ASR systems of high performance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.81-89
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• 2019

As the need for the integration of administrative datasets and address information increases, there is also growing interest in POI (Point of Interest) data as a source of location information across applications and platforms. The purpose of this study is to develop an alias database management method for efficient POI searching, based on POI data representing position. First, we determine the attributes of POI alias data as it is used variously by individual users. When classifying aliases of POIs, we excluded POIs in which the typo and names are all in English alphabet. The attributes of POI aliases are classified into four categories, and each category is reclassified into three classes according to the strength of the attributes. We then define the quality of POI aliases classified in this study through experiments. Based on the four attributes of POI defined in this study, we developed a method of managing one POI alias through and integrated method composed of word embedding and a similarity measurement. Experimental results of the proposed POI alias management method show that it is possible to utilize the algorithm developed in this study if there are small numbers of aliases in each POI with appropriate POI attributes defined in this study.

• Journal of KIISE:Software and Applications
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• v.34 no.2
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• pp.104-111
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• 2007

This paper examines how the performance of an automatic speech recognizer was improved for Korean Point-of-Interest (POI) data by modeling pronunciation variation using structural prosodic information such as prosodic words and syllable length. First, multiple pronunciation variants are generated using prosodic words given that each POI word can be broken down into prosodic words. And the cross-prosodic-word variations were modeled considering the syllable length of word. A total of 81 experiments were conducted using 9 test sets (3 baseline and 6 proposed) on 9 trained sets (3 baseline, 6 proposed). The results show: (i) the performance was improved when the pronunciation lexica were generated using prosodic words; (ii) the best performance was achieved when the maximum number of variants was constrained to 3 based on the syllable length; and (iii) compared to the baseline word error rate (WER) of 4.63%, a maximum of 8.4% in WER reduction was achieved when both prosodic words and syllable length were considered.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.321-328
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• 2017

We have implemented a technique to correct the brightness, saturation, and contrast of an image according to the degree of light, and further compensate the backlight. Backlight compensation can be done automatically or manually. For manual backlight compensation, we have to select the region of interest (ROI). ROI can be selected by connecting the outline of the desired object. We make users select the region delicately with the new magnetic lasso tool. The previous lasso tool has a disadvantage that the start point and the end point must be connected. However, the proposed lasso tool has the advantage of selecting the region of interest without connecting the start point and the end point. We can automatically obtain various results of backlight compensation by adjusting the number of k-means clusters for texture extraction and the threshold value for binarization.

• Journal of Digital Contents Society
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• v.19 no.5
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• pp.871-880
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• 2018

Recently, the technology of recommendation of POI (Point of Interest) related technology is getting attention with the increase of big data related to consumers. Previous studies on POI recommendation systems have been limited to specific data sets. The problem is that if the study is carried out with this particular dataset, it may be suitable for the particular dataset. Therefore, this study analyzes the similarity and correlation between stores using the user visit data obtained from the integrated sensor installed in Seoul and Songjeong roads. Based on the results of the analysis, we study the preference prediction system which recommends the stores that new users are interested in. As a result of the experiment, various similarity and correlation analysis were carried out to obtain a list of relevant stores and a list of stores with low relevance. In addition, we performed a comparative experiment on the preference prediction accuracy under various conditions. As a result, it was confirmed that the jacquard similarity based item collaboration filtering method has higher accuracy than other methods.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.154-161
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• 2021

The purpose of this study is to investigate the effect of college students' interest in sports media on sports values and sports activities. In order to identify the purpose of this study, college students aged 20 years or older living in Jeonnam region in 2021 were selected as the population. A total of 300 subjects (150 males and 150 females) were selected using the convenient sampling method. The survey tool consisted of a questionnaire on a 5-point scale. Also, the collected data were statistically processed using SPSS version 20.0. The results obtained through this research procedure are as follows. First, it was found that college students' interest in sports media had a partial influence on sports values. Second, it was found that college students' interest in sports media partially affected their participation in sports. Third, it was found that college students' participation in sports had a partial effect on sports values.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.511-520
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• 2021

Over the last decade, Bitcoin has attracted a great deal of public interest and Bitcoin market has grown rapidly. One of the main characteristics of the market is that it often undergoes some events or incidents that cause outlying observations. To obtain reliable results in the statistical analysis of Bitcoin data, these outlying observations need to be carefully treated. In this study, we are interested in change point analysis for Bitcoin return series having such outlying observations. Since these outlying observations can affect change point analysis undesirably, we use a robust test for parameter change to locate change points. We report some significant change points that are not detected by the existing tests and demonstrate that the model allowing for parameter changes is better fitted to the data. Finally, we show that the model with parameter change can improve the forecasting performance of Value-at-Risk.