• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.23-29
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• 2017

A concept of a VSA (Virtual Source Array) is the method for an acoustic spatio-temporal focus at a selected location in the outbound direction with respect to the VSA without the need of a probe source as combines a TRP (Time-Reversal Processing) and time-delay and beam-steering. However, in TRP using the VSA concept, it is limited to the critical angle and the short distances relevant to the VSA. In this paper, the waveguide invariant theory is applied to the VSA concept to refocus the received field at ranges greater other than the critical angle and the short ranges by shifting the focused field. The suggested method is verified via numerical simulation, and the results show that the robust acoustic focusing is achieved on the selected location regardless of the limitation on the conventional VSA concept.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.31 no.2 s.51
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• pp.179-187
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• 2005

The reduced production of domestic cosmetics in 2003, compared to last 5 years shows the recession of cosmetics industry. Under this situation, there has been reorganization on the domestic cosmetic market that low-end cosmetic .products become a trend due to the fact that major cosmetic companies also focus on low-end market since the last half year of 2004. However, it does not seem to be a temporal fashion that the extremely low-end cosmetics had an impact wavelength on cosmetics market. It has important meaning for the brand product strategy. This research focused on analysis of market situation and strategy through investigation of requirement and satisfaction on extremely low-end cosmetics in order to keep and improve it, which stimulated depressed cosmetic market.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.67-78
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• 2008

With the rapid development of wireless communication and mobile equipment, many applications for location-based services have been emerging. Moving objects such as vehicles and ships change their positions over time. Moving objects have their moving path, called the trajectory, because they move continuously. To monitor the trajectory of moving objects in a large scale database system, an efficient Indexing scheme to processed queries related to trajectories is required. In this paper, we focus on the issues of minimizing the dead space of index structures. The Minimum Bounding Boxes (MBBs) of non-leaf nodes in trajectory-preserving indexing schemes have large amounts of dead space since trajectory preservation is achieved at the sacrifice of the spatial locality of trajectories. In this thesis, we propose entry relocating techniques to reduce dead space and overlaps in non-leaf nodes. we present performance studies that compare the proposed index schemes with the TB-tree and the R*-tree under a varying set of spatio-temporal queries.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.221-237
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• 2010

To estimate marine primary production, satellite data are essential for providing much better spatial and temporal resolutions. However, primary production estimation for turbid coastal water such as the Yellow Sea still needs much improvement. Here we evaluate currently available methods of primary production estimation in the Yellow Sea. We focus on comparison of eight combinations from four chlorophyll-a algorithms and two primary production algorithms of the Yellow Sea. Estimated primary production by the eight combinations ranged from 96.5 to $610.2\;gC\;m^{-2}\;yr^{-1}$ in the central region of the Yellow Sea. The new chlorophyll algorithms (presently under development by Korea, China, and Japan scientists) are expected to improve the retrieval of chlorophyll-a in turbid regions compared to the standard algorithm but there are certain unresolved problems. The new algorithm for primary production (which uses adjusted physiological parameters with in-situ data) also needs further improvement.

• Phonetics and Speech Sciences
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• v.11 no.3
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• pp.31-38
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• 2019

The current electromagnetic articulography study analyzes several articulatory measures and examines whether, and if so, how they are interconnected, with a focus on cluster types and an additional consideration of speech rates and morphosyntactic contexts. Using articulatory data on non-assimilating contexts from three Seoul-Korean speakers, we examine how speaker-dependent gestural overlap between C1 and C2 in a low vowel context (/a/-to-/a/) and their resulting intergestural coordination are realized. Examining three C1C2 sequences (/k(#)t/, /k(#)p/, and /p(#)t/), we found that three normalized gestural overlap measures (movement onset lag, constriction onset lag, and constriction plateau lag) were correlated with one another for all speakers. Limiting the scope of analysis to C1 velar stop (/k(#)t/ and /k(#)p/), the results are recapitulated as follows. First, for two speakers (K1 and K3), i) longer normalized constriction plateau lags (i.e., less gestural overlap) were observed in the pre-/t/ context, compared to the pre-/p/ (/k(#)t/>/k(#)p/), ii) the tongue dorsum at the constriction offset of C1 in the pre-/t/ contexts was more anterior, and iii) these two variables are correlated. Second, the three speakers consistently showed greater horizontal distance between the vertical tongue dorsum and the vertical tongue tip position in /k(#)t/ sequences when it was measured at the time of constriction onset of C2 (/k(#)t/>/k(#)p/): the tongue tip completed its constriction onset by extending further forward in the pre-/t/ contexts than the uncontrolled tongue tip articulator in the pre-/p/ contexts (/k(#)t/>/k(#)p/). Finally, most speakers demonstrated less variability in the horizontal distance of the lingual-lingual sequences, which were taken as the active articulators (/k(#)t/=/k(#)p/ for K1; /k(#)t/

• Korean Journal of Cognitive Science
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• v.30 no.1
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• pp.51-83
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• 2019

Delay of immediate gains/losses brings on additional gaines/losses as much as waiting period. However, there are individual difference in evaluating the value of delayed time discounting on the person. In this study, to investigates the individual differences about valuating the delayed time, it is ascertained the correlation between decisions from intertemporal choice task and individual differences of risk taking/perception, emotion, regulatory focus, and HPSP and BELT, subjective period measuring task. In Addition, it is analyzed the individual differences after classifying good/bad performer of intertemporal tasks and person who perceive long/short about the future periods. As a result, good performers of intertemporal task have high openness and perceive longer about 12 hours, 15 days, 6 months and 5 years. Reconstruction about future temporal length plays an important role on intertemporal task, and it is discussed about necessity of follow up study.

• Forest Science and Technology
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• v.14 no.4
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• pp.181-191
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• 2018

This study was carried out in the teaching and research forest of the University of Dschang in Belabo, with the aim of analysing land-cover and land-use changes as well as carbon stocks dynamic. The databases used are composed of three Landsat satellite images (5TM of 1984, 7ETM + of 2000 and 8OLI of 2016), enhanced by field missions. Satellite images were processed using ENVI and ArcGIS software. Interview, focus group discussion methods and participatory mapping were used to identify the activities carried out by the local population. An inventory design consisting of four transects was used to measure dendrometric parameters and to identify land-use types. An estimation of carbon stocks in aboveground and underground woody biomass was made using allometric models based on non-destructive method. Dynamic of land-cover showed that the average annual rate of deforestation is 0.48%. The main activities at the base of this change are agriculture, house built-up and logging. Seven types of land-use were identified; adult secondary forests (64.10%), young secondary forests (7.54%), wetlands (7.39%), fallows (3.63%), savannahs (9.59%), cocoa farms (4.28%) and mixed crop farms (3.47%). Adult secondary forests had the highest amount of carbon ($250.75\;t\;C\;ha^{-1}$). This value has decreased by more than 60% for mixed crop farms ($94.67\;t\;C\;ha^{-1}$), showing the impact of agricultural activities on both forest cover and carbon stocks. Agroforestry systems that allow conservation and introduction of woody species should be encouraged as part of a participatory management strategy of this forest.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.51-60
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• 2021

Effective nonpoint source (NPS) pollution management requires frequent water quality monitoring, which is, however, often costly to be implemented in practice. Statistical techniques and machine learning methods allow us to identify and focus on fundamental environmental variables that have close relationships with NPS pollutants of interest. This study developed surrogate models to predict the concentrations of suspended sediment (SS) and total phosphorus (T-P) from turbidity and runoff discharge rates using multiple linear regression (MLR) and random forest (RF) methods. The RF models provided acceptable performance in predicting SS and T-P, especially when runoff discharge rates were high. The RF models outperformed the MLR models in all the cases. Such finding highlights the potential of RF techniques and models as a tool to identify fundamental environmental variables that are measured in relatively inexpensive ways or freely available but still able to provide information required to quantify the concentrations of NP S pollutants. The analysis of relative importance rates showed that the temporal variations of SS and T-P concentrations could be more effectively explained by that of turbidity than runoff discharge rate. This study demonstrated that the advanced statistical techniques such as machine learning could help to improve the efficiency of NPS pollutants monitoring.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.62-70
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• 2022

This study investigates the temporal structure and movement of floating people near university areas in Daegu metropolitan city, South Korea, before and after Covid-19. In order to determine Daegu's position, the current study compares Daegu and Seoul. The floating population is used as an index to reveal people's various activities in the area known as the local business district, which surrounds the university campus. The information was provided by mobile phone manufacturers. A municipal authority managed a public website where mobile data was made available. Several statistical and visualization techniques were used after the data pre-processing steps. As a result, the floating population fluctuation patterns in both cities in the first half of 2019 and 2020 were comparable. When the Covid-19 diffusion rate in Daegu stabilized in the second half of 2020, the floating population in Daegu increased slightly over the previous year, while the population in Seoul decreased due to the second wave of Covid-19.

• Journal of IKEEE
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• v.26 no.1
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• pp.62-66
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• 2022

Recently, there have been many research efforts based on data-based deep learning technologies to deal with the interference problem between heterogeneous wireless communication devices in unlicensed frequency bands. However, existing approaches are commonly based on the use of complex neural network models, which require high computational power, limiting their efficiency in resource-constrained network interfaces and Internet of Things (IoT) devices. In this study, we address the problem of classifying heterogeneous wireless technologies including Wi-Fi and ZigBee in unlicensed spectrum bands. We focus on a data-driven approach that employs a supervised-learning method that uses received signal strength indicator (RSSI) data to train Deep Convolutional Neural Networks (CNNs). We propose a simple measurement methodology for collecting RSSI training data which preserves temporal and spectral properties of the target signal. Real experimental results using an open-source 2.4 GHz wireless development platform Ubertooth show that the proposed sampling method maintains the same accuracy with only a 10% level of sampling data for the same neural network architecture.