• Knowledge Management Research
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• v.23 no.2
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• pp.123-142
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• 2022

The non-face-to-face environment accelerated by COVID-19 has speeded up the dissemination of digital virtual ecosystems and metaverse. In order for the metaverse to be sustainable, digital twins that are compatible with the real world are key, and critical technology for that is AR (Augmented Reality). In this study, we examined research trends about AR, and will propose the directions for future AR research. We conducted LDA based topic modeling on 11,049 abstracts of published domestic and foreign AR related papers from 2009 to Mar 2022, and then looked into AR that was comprehensive research trends, comparison of domestic and foreign research trends, and research trends before and after the popularity of metaverse concepts. As a result, the topics of AR related research were deduced from 11 topics such as device, network communication, surgery, digital twin, education, serious game, camera/vision, color application, therapy, location accuracy, and interface design. After popularity of metaverse, 6 topics were deduced such as camera/vision, training, digital twin, surgical/surgical, interaction performance, and network communication. We will expect, through this study, to encourage active research on metaverse AR with convergent characteristics in multidisciplinary fields and contribute to giving useful implications to practitioners.

• Analytical Science and Technology
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• v.27 no.1
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• pp.34-40
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• 2014

SPLITT fractionation (SF) allows continuous (and thus a preparative scale) separation of micronsized particles into two size fractions ('fraction-a' and 'fraction-b'). SF is usually carried out in a thin rectangular channel with two inlets and two outlets, which is equipped with flow stream splitters at the inlet and the outlet of the channel, respectively. A new large scale splitter-less gravitational SF (GSF) system had been assembled, which was designed to eliminate the flow stream splitters and thus is operated by the full feed depletion (FFD) mode (FFD-GSF). In the FFD mode, there is only one inlet through which the sample is fed. There is no carrier liquid fed into the channel, and thus prevents the sample dilution. The effects of the sample-feeding flow rate, the channel thickness on the fractionation efficiency (FE, number % of particles that have the size predicted by theory) of FFD-GSF was investigated using industrial polyurethane (PU) latex beads. The carrier liquid was water containing 0.1% FL-70 (particle dispersing agent) and 0.02% sodium azide (used as bactericide). The sample loading rate was varied from about 4 to 7 L/hr with the sample concentration fixed at 0.01%. The GSF channel thickness was varied from 900 to $1300{\mu}m$. Particles exiting the GSF channel were collected and monitored by optical microscopy (OM). Sample recovery was monitored by collecting the fractionated particles on a $0.45{\mu}m$ membrane filter. It was found that FE of fraction-a was increased as the channel thickness increases, and FE of fraction-b was increased as the flow rate was increased. In all cases, the sample recovery has higher than 95%. It seems the new splitter-less FFD GSF system could become a useful tool for large scale separations of various types of micron-sized particles.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.69-93
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• 2012

Various influence-related relationships in Social Network Services (SNS) among users, posts, and user-and-post, can be expressed using links. The current research evaluates the influence of specific users or posts by analyzing the link structure of relevant social network graphs to identify influential users. We applied the concept of mutual interactions proposed for ranking semantic web resources, rather than the voting notion of Page Rank or HITS, to blogosphere, one of the early SNS. Through many experiments with network models, where the performance and validity of each alternative approach can be analyzed, we showed the applicability and strengths of our approach. The weight tuning processes for the links of these network models enabled us to control the experiment errors form the link weight differences and compare the implementation easiness of alternatives. An additional example of how to enter the content scores of commercial or spam posts into the graph-based method is suggested on a small network model as well. This research, as a starting point of the study on identifying influential users in SNS, is distinctive from the previous researches in the following points. First, various influence-related properties that are deemed important but are disregarded, such as scraping, commenting, subscribing to RSS feeds, and trusting friends, can be considered simultaneously. Second, the framework reflects the general phenomenon where objects interacting with more influential objects increase their influence. Third, regarding the extent to which a bloggers causes other bloggers to act after him or her as the most important factor of influence, we treated sequential referencing relationships with a viewpoint from that of PageRank or HITS (Hypertext Induced Topic Selection).

• Progress in Medical Physics
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• v.8 no.2
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• pp.67-76
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• 1997

We studied optical behavior of scintillation light generated in NaI(TI) crystal using Monte Carlo simulation method. The simulation was performed for the model of NaI(TI) scintillator (size: 60 mm ${\times}$ 60 mm ${\times}$ 6 mm) using an optical tracking code. The sensitivity as a function of surface treatment (Ground, Polished, Metal-0.95RC, Polished-0.98RC, Painted- 0.98RC) of the incident surface of the scintillator was compared. The effects of NaI(TI) scintillator thickness and the refractive index of light guide optically coupling between the NaI(TI) scintillator and photomultiplier tube (PMT) were simulated. We also evaluated intrinsic position resolution of the system by calculating the spread of scintillation light generated. The sensitivities of the system having the surface treatment of Ground, Polished, Metal-0.95RC, Polished-0.98RC and Painted-0.98RC were 70.9％, 73.9％, 78.6％, 80.1％ and 85.2％, respectively, and the surface treatment of Painted-0.98RC allowed the highest sensitivity. As increasing the thickness of scintillation crystal and light guide, the sensitivity of the system was decreased. As the refractive index of light guide increases, the sensitivity was increased. The intrinsic position resolution of the system was estimated to be 1.2 mm in horizontal and vertical directions. In this study, the performance of NaI(TI)-PMT detector system was evaluated using Monte Carlo simulation. Based on the results, we concluded that the NaI(TI)-PMT detector array is a favorable configuration for small gamma camera imaging breast tumor using Tc-99m labeled radiopharmaceuticals.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.3
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• pp.41-48
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• 1965

This study was aimed at knowing the magnitude of year variation in rice heading dates under the different seasonal cultures, and to estimate the heading date in advance. Using six rice varieties such as Kwansan, Suwon＃82, Suwon ＃144, Norin＃17, Yukoo＃132 and Paltal, the early, ordinary and late seasonal cultures had been carried out at Paddy Crop Division, Crop Experiment Station at Suwon for the six-year period 1959 to 1964. In addition the data of the standard rice cultures at the Provincial Offices of Rural Development for the 12-year period 1953 to 1954, were analyzed for the purpose of clarifying a relationship between variation of rice heading dates and some of meteorological data related to the locations and years. The results of this study are as follows: 1. Year variation of rice heading dates was as high as 14 to 21 days in the early seasonal culture and 7 to 14 days in the ordinary seasonal culture, while as low as one to seven days in the late seasonal culture which was the lowest among three cultures. The magnitude of variation depended greatly on variety, cultural season and location. 2. It was found out that there was a close negative correlation between the accumulated average air temperature for 40 days from 31 days after seeding and number of days to heading in the early seasonal culture. Accordingly, it was considered possible to predict the rice heading date through calculation of the accumulated average air temperature for the above period and then the linear regression(Y=a+bx). On the other hand, an estimation of the heading date in the late seasonal culture requires for the further studies. In the ordinary seasonal culture, no significant correlation between the accumulated average air temperature and number of days to heading was obtained in the six-year experiments conducted at Suwon. There was a varietal difference in relationship between the accumulated average air temperature for 70 days from seeding and number of days to heading in the standard cultures at the provincial offices of rural development. Some of varieties showed a significant correlation between two factors while the others didn't show any significant correlation. However, there was no regional difference in this relationship.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.