• Journal of Information Processing Systems
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• v.12 no.3
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• pp.525-537
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• 2016

Data hiding is a wide field that is helpful to secure network communications. It is common that many data hiding researchers consider improving and increasing many aspects such as capacity, stego file quality, or robustness. In this paper, we use an audio file as a cover and propose a reversible steganographic method that is modifying the sample values using modulus function in order to make the reminder of that particular value to be same as the secret bit that is needed to be embedded. In addition, we use a location map that locates these modified sample values. This is because in reversible data hiding it needs to exactly recover both the secret message and the original audio file from that stego file. The experimental results show that, this method (measured by correlation algorithm) is able to retrieve exactly the same secret message and audio file. Moreover, it has made a significant improvement in terms of the following: the capacity since each sample value is carrying a secret bit. The quality measured by peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR), Pearson correlation coefficient (PCC), and Similarity Index Modulation (SIM). All of them have proven that the quality of the stego audio is relatively high.

• Journal of Information Management
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• v.40 no.2
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• pp.95-115
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• 2009

Author resolution is to disambiguate same-name author occurrences into real individuals. For this, pair-wise author similarities are computed for author name entities, and then clustering is performed. So far, many studies have employed hierarchical clustering techniques for author disambiguation. However, various hierarchical clustering methods have not been sufficiently investigated. This study covers an empirical evaluation and analysis of hierarchical clustering applied to Korean author resolution, using multiple distance functions such as Dice coefficient, Cosine similarity, Euclidean distance, Jaccard coefficient, Pearson correlation coefficient.

• Journal of the Korean Home Economics Association
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• v.24 no.4
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• pp.189-197
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• 1986

The primary purpose of this study was to investigate the nature and relationship of attitudes of mothers and their daughters concerning the value of children. the secondary interest was to compare this study with the American studies done by Bormann & Stockdale(1979), and Leavy & Hough(1983). Subjects for the study were college-age daughters their married sisters, and their mothers. The“Fawcett Opinions about Children Questionnair”was used to measure beliefs about children. Pearson Product Moment Correlations were computed for mother-daughter(married), mother-daughter(unmarried), and daughter(married)-daughter (unmarried) on each of nine subscales on value of children. To study the generation differences and marriage differences, matched sample t-test were carried. Several significant relationships were found for mother-daughter (married), daughter(married)-daughter (unmarried) pairs. Only one significant relationship was found for mother-daughter(unmarried) pairs. Significant differences were found between mother's group and daughters' groups on most subscales except one or two (generation effect). Significant differences were found between married daughters and unmarried daughters on 4 subscales(marriage effect). The results did not corroborate the findings of American studies which revealed the lack of congruence between mother and daughter attitudes. It was noted that as daughters had children themselves, their attitudes toward children had become more congruent with their mothers. There was also evidence to support the generation differences between mothers and daughters values. It was concluded that both value similarity and generation differences vary as a function of the particular events as well as age-itself.

• Smart Media Journal
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• v.5 no.2
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• pp.84-89
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• 2016

For a place-recommendation model based on user's behavior and multi-attribute attitude in this thesis. We focus groups that show similar patterns of visiting restaurants and then compare one and the other. We make use of The Fishbein Equation, Pearson's Correlation Coefficient to calculate multi-attribute attitude scores. Furthermore, We also make use of Preference Prediction Algorithm and Distance based method named "Euclidean Distance" to provide accurate results. We can demonstrate how excellent this system is through several experiments carried out with actual data.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.645-654
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• 2019

The purpose of this study was to collect and analyze personal bio data and social network services (SNS) data, derive user preference and user life pattern, and propose intuitive and precise user modeling. This study not only tried to conduct eye tracking experiments using various smart devices to be the ground of the recommendation system considering the attribute of smart devices, but also derived classification preference by analyzing eye tracking data of collected bio data and SNS data. In addition, this study intended to combine and analyze preference of the common classification of the two types of data, derive final preference by each smart device, and based on user life pattern extracted from final preference and collected bio data (amount of activity, sleep), draw the similarity between users using Pearson correlation coefficient. Through derivation of preference considering the attribute of smart devices, it could be found that users would be influenced by smart devices. With user modeling using user behavior pattern, eye tracking, and user preference, this study tried to contribute to the research on the recommendation system that should precisely reflect user tendency.

• Fisheries and Aquatic Sciences
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• v.26 no.6
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• pp.393-405
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• 2023

The aim of this research was to enhance the flavor of visceral extracts from skipjack tuna. Flavor precursors and the optimum condition for the Maillard reaction were determined. The flavor extract was prepared from the tuna viscera using Endo/Exo Protease controlled in 3 factors; temperature, enzyme amounts and incubation time. The optimal condition for producing tuna viscera protein hydrolysate (TVPH) was 60℃, 0.5% enzyme (w/w) and 4-hour incubation time. TVPH were further processed to tuna viscera flavor enhancer (TVFE) with Maillard reaction. The Maillard reactions of TVFE were conducted with or without supplements such as xylose, yeast extract and methionine. The Maillard volatile components were analyzed with gas chromatography-mass spectrometry. Sixteen volatiles such as 2-methylpropanal, methylpyrazine, 2,5-dimethylpyrazine, dimethyl disulfide and 2-acetylthaizone were newly formed via Maillard reaction and the similarity of volatile contents from TVPH and TVFE were virtualized using Pearson's correlation integrated with heat-map and principal component analysis. To virtualize aromagram of TVPH and TVFE, odor activity value and odor impact spectrum (OIS) techniques were applied. According to OIS results, 3-methylbutanal, 2-methylbutanal, 1-octen-3-ol 2,5-dimethylpyrazine, methional and dimethyl trisulfide were the potent odorants contributed to the meaty, creamy, and toasted aroma in TVFE.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.714-717
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• 2008

협업여과 추천기법에는 사용자 기반 협업여과와 아이템 기반 협업여과가 있으며, 절차는 유사도 측정, 이웃 선정, 예측값 생성 단계로 이루어진다. 유사도 측정 단계에는 유클리드 거리(Euclidean Distance), 코사인 유사도(Cosine Similarity), 피어슨 상관계수(Pearson Correlation Coefficient) 방법 등이 있고, 이웃 선정 단계에는 상관 한계치(Correlation-Threshold), 근접 N 이웃(Best-N-Neighbors) 방법 등이 있다. 마지막으로 예측값 생성 단계에는 단순평균(Simple Average), 가중합(Weighted Sum), 조정 가중합(Adjusted Weighted Sum) 등이 있다. 이처럼 협업여과 추천기법에는 다양한 기법들이 사용되고 있다. 따라서 본 논문에서는 사용자 기반 협업여과와 아이템 기반 협업여과 추천기법에 사용되는 유사도 측정 기법과 예측값 생성 기법의 최적화된 조합을 알아보기 위해 성능 실험 및 비교 분석을 하였다. 실험은 GroupLens의 MovieLens 데이터 셋을 활용하였고 MAE(Mean Absolute Error)값을 이용하여 추천기법을 비교 하였다. 실험을 통해 유사도 측정 기법과 예측값 생성 기법의 최적화된 조합을 찾을 수 있었고, 사용자 기반 협업여과와 아이템 기반 협업여과의 성능비교를 통해 아이템 기반 협업여과의 성능이 보다 우수했음을 확인 하였다.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.277-287
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• 2014

In LBSNS(Location-based Social Network Service), users can share locations and communicate with others by using check-in data. The check-in data consists of POI name, category, coordinate and address of locations, nickname of users, evaluating grade of locations, related article/photo/video, and etc. If you analyze the check-in data from the location-based social network service in accordance with your situation, you can provide various customized services. Therefore, In this paper, we develop a location recommendation system based on LBSNS that can utilize the check-in data efficiently. This system analyzes the location category of the check-in data, determines the weighted value of it, and finds out the similarity between users by using the Pearson correlation coefficient. Also, it obtains the preference score of recommended locations by using the collaborated filtering algorithm and then, finds out the distance score by applying the Euclidean's algorithm to the recommended locations and the current users' locations. Finally, it recommends appropriate locations by applying the weighted value to the preference score and the distance score. In addition, this paper approved excellence of the proposed system throughout the experiment using real data.

• Journal of Korean Society of Forest Science
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• v.96 no.2
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• pp.227-234
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• 2007

The forest canopy gap has been well known as a substantial process of forest cyclic regeneration and important role in stand structure, dynamics, and biodiversity of the forest ecosystem. Based on 3,600 $5m{\times}5m$ square grids in a 9ha permanent experimental plot, the study was conducted to evaluate the regeneration pattern of woody species by developmental stage {seedlings (<1 m of height), saplingI (>1 m of height, <2 cm of DBH), and saplingII (2 cm$<200m^2$), $201-400m^2$, $400-600m^2$, $601-800m^2$, and $>800m^2$) in the mixed broadleaved-Korean pine forest. The results indicated that the regenerating trees of Populus ussuriensis occurred only in the canopy gap area, considered to be a typical gap-dependent species. The regeneration of Ulmus japonica, Ulmus laciniata, and Maackia amurensis could be generally satisfied with the gap size of $201-600m^2$, Betula costata and Prunus padus with gap size of $401-800m^2$, Picea koraiensis with gap size of $201-800m^2$, Fraxinus mandshurica and Syringa reticulata var. mandshurica with smaller than $800m^2$, respectively. Acer ukurunduense and Acer tegmentosum were likely to have no problem with the gap size to make gap regeneration. Acer mono and Tilia amurensis looked more capable of regenerating in the closed canopy disregarding the upper crown condition. The regeneration of Pinus koraiensis and Abies nephrolepis had no trouble under the canopy condition in less than $800m^2$of gap size. The density of regenerating shrubs was rather high, especially under the closed canopy, considered to be associated with great amount of regeneration production in such shade tolerant species as Lonicera maackii, Corylus mandshurica, Euonymus pauciflorus, and Philadelphus schrenkii under the closed canopy. Pearson correlation coefficient was computed to compare the similarity among non-gap area and five gap size classes by developmental stages for trees and shrubs. The similarity coefficients among closed canopy and the gap size classes were mostly significantly correlated to each other with a few exceptions.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.2
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• pp.174-188
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• 2004

In the life environment changed with not only the quality and the price of the products but also the material abundance, it is the most crucial factor for the strategy of product sales to investigate consumer's sensibility and preference degree. In this perspective, it is necessary to design and merchandise the products in cope with each consumer's sensibility and needs as well as its functional aspects. In this paper, we propose the Fashion Design Recommender Agent System (FDRAS-pro) for textile design applying collaborative filtering personalization technique as one of the methods of material development centered on consumer's sensibility and preference. For a collaborative filtering system based on textile, Representative-Attribute Neighborhood is adopted to determine the number or neighbors that will be used for preferences estimation. Pearson's Correlation Coefficient is used to calculate similarity weights among users. We build a database founded on the sensibility adjectives to develop textile designs by extracting the representative sensibility adjectives from users' sensibility and preferences about textile designs. FDRAS-pro recommends textile designs to a customer who has a similar propensity about textile. To investigate the sensibility and emotion according to the effect of design factors, fertile designs were analyzed in terms of 9 design factors, such as, motif source, motif-background ratio, motif variation, motif interpretation, motif arrangement, motif articulation, hue contrast, value contrast, chroma contrast. Finally, we plan to conduct empirical applications to verify the adequacy and the validity of our system.