• Geophysics and Geophysical Exploration
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• v.5 no.4
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• pp.223-235
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• 2002

Since weak Bones or geological lineaments are likely to be eroded, there may develop weak Bones beneath rivers, and a careful evaluation of ground condition is important to construct structures passing through a river. DC resistivity method, however, has seldomly applied to the investigation of water-covered area, possibly because of difficulties in data aquisition and interpretation. The data aquisition having high quality may be the most important factor, and is more difficult than that in land survey, due to the water layer overlying the underground structure to be imaged. Through the numerical modeling and the analysis of a case history, we studied the method of resistivity survey at the water-covered area, starting from the characteristics of measured data, via data acquisition method, to the interpretation method. We unfolded our discussion according to the installed locations of electrodes, ie., floating them on the water surface, and installing them at the water bottom, because the methods of data acquisition and interpretation vary depending on the electrode location. Through this study, we could confirm that the DC resistivity method can provide fairly reasonable subsurface images. It was also shown that installing electrodes at the water bottom can give the subsurface image with much higher resolution than floating them on the water surface. Since the data acquired at the water-covered area have much lower sensitivity to the underground structure than those at the land, and can be contaminated by the higher noise, such as streaming potential, it would be very important to select the acquisition method and electrode array being able to provide the higher signal-to-noise ratio (S/N ratio) data as well as the high resolving power. Some of the modified electrode arrays can provide the data having reasonably high S/N ratio and need not to install remote electrode(s), and thus, they may be suitable to the resistivity survey at the water-covered area.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.1
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• pp.94-131
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• 2007

A review on the papers published in the Korean Journal of Air-Conditioning and Refrigerating Engineering in 2004 and 2005 has been done. Focus has been put on current status of research in the aspect of heating, cooling, air-conditioning, ventilation, sanitation and building environment. The conclusions are as follows. (1) Most of fundamental studies on fluid flow were related with heat transportation of facilities. Drop formation and rivulet flow on solid surfaces were interesting topics related with condensation augmentation. Research on micro environment considering flow, heat, humidity was also interesting for comfortable living environment. It can be extended considering biological aspects. Development of fans and blowers of high performance and low noise were continuing topics. Well developed CFD and flow visualization(PIV, PTV and LDV methods) technologies were widely applied for developing facilities and their systems. (2) The research trends of the previous two yews are surveyed as groups of natural convection, forced convection, electronic cooling, heat transfer enhancement, frosting and defrosting, thermal properties, etc. New research topics introduced include natural convection heat transfer enhancement using nanofluid, supercritical cooling performance or oil miscibility of $CO_2$, enthalpy heat exchanger for heat recovery, heat transfer enhancement in a plate heat exchanger using fluid resonance. (3) The literature for the last two years($2004{\sim}2005$) is reviewed in the areas of heat pump, ice and water storage, cycle analysis and reused energy including geothermal, solar and unused energy). The research on cycle analysis and experiments for $CO_2$ was extensively carried out to replace the Ozone depleting and global warming refrigerants such as HFC and HCFC refrigerants. From the year of 2005, the Gas Engine Heat Pump(GHP) has been paid attention from the viewpoint of the gas cooling application. The heat pipe was focused on the performance improvement by the parametric analysis and the heat recovery applications. The storage systems were studied on the performance enhancement of the storage tank and cost analysis for heating and cooling applications. In the area of unused energy, the hybrid systems were extensively introduced and the life cycle cost analysis(LCCA) for the unused energy systems was also intensively carried out. (4) Recent studies of various refrigeration and air-conditioning systems have focused on the system performance and efficiency enhancement. Heat transfer characteristics during evaporation and condensation are investigated for several tube shapes and of alternative refrigerants including carbon dioxide. Efficiency of various compressors and expansion devices are also dealt with for better modeling and, in particular, performance improvement. Thermoelectric module and cooling systems are analyzed theoretically and experimentally. (5) According to the review of recent studies on ventilation systems, an appropriate ventilation systems including machenical and natural are required to satisfied the level of IAQ. Also, an recent studies on air-conditioning and absorption refrigeration systems, it has mainly focused on distribution and dehumidification of indoor air to improve the performance were carried out. (6) Based on a review of recent studies on indoor environment and building service systems, it is noticed that research issues have mainly focused on optimal thermal comfort, improvement of indoor air Quality and many innovative systems such as air-barrier type perimeter-less system with UFAC, radiant floor heating and cooling system and etc. New approaches are highlighted for improving indoor environmental condition as well as minimizing energy consumption, various activities of building control and operation strategy and energy performance analysis for economic evaluation.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.53-65
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• 2019

Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

• Korean Journal of Ecology and Environment
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• v.42 no.2
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• pp.200-211
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• 2009

A mathematical modeling program called Soil and Water Assessment Tool (SWAT) developed by USDA was applied to Kyongan stream watershed. It was run under BASINS (Better Assessment Science for Integrating point and Non-point Sources) program, and the model was calibrated and validated using KTMDL monitoring data of 2004${\sim}$2008. The model efficiency of flow ranged from very good to fair in comparison between simulated and observed data and it was good in the water quality parameters like flow range. The model reliability and performance were within the expectation considering complexity of the watershed and pollutant sources. The results of pollutant loads estimation as yearly (2004${\sim}$2008), pollutant loadings from 2006 were higher than rest of year caused by high precipitation and flow. Average non-point source (NPS) pollution rates were 30.4%, 45.3%, 28.1% for SS, TN and TP respectably. The NPS pollutant loading for SS, TN and TP during the monsoon rainy season (June to September) was about 61.8${\sim}$88.7% of total NPS pollutant loading, and flow volume was also in a similar range. SS concentration depended on precipitation and pollution loading patterns, but TN and TP concentration was not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. SWAT based on BASINS was applied to the Kyongan stream watershed successfully without difficulty, and it was found that the model could be used conveniently to assess watershed characteristics and to estimate pollutant loading including point and non-point sources in watershed scale.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.5-22
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• 2021

This study aimed to understand how people perceive the transition from offline to online classes at universities during the COVID-19 pandemic. To achieve the goal, we collected tweets related to online classes on Twitter and performed sentiment and time series topic analysis. We have the following findings. First, through the sentiment analysis, we found that there were more negative than positive opinions overall, but negative opinions had gradually decreased over time. Through exploring the monthly distribution of sentiment scores of tweets, we found that sentiment scores during the semesters were more widespread than the ones during the vacations. Therefore, more diverse emotions and opinions were showed during the semesters. Second, through time series topic analysis, we identified five main topics of positive tweets that include class environment and equipment, positive emotions, places of taking online classes, language class, and tests and assignments. The four main topics of negative tweets include time (class & break time), tests and assignments, negative emotions, and class environment and equipment. In addition, we examined the trends of public opinions on online classes by investigating the changes in topic composition over time through checking the proportions of representative keywords in each topic. Different from the existing studies of understanding public opinions on online classes, this study attempted to understand the overall opinions from tweet data using sentiment and time series topic analysis. The results of the study can be used to improve the quality of online classes in universities and help universities and instructors to design and offer better online classes.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1135-1147
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• 2021

In order to geometrically correct high-resolution satellite imagery, the sensor modeling process that restores the geometric relationship between the satellite sensor and the ground surface at the image acquisition time is required. In general, high-resolution satellites provide RPC (Rational Polynomial Coefficient) information, but the vendor-provided RPC includes geometric distortion caused by the position and orientation of the satellite sensor. GCP (Ground Control Point) is generally used to correct the RPC errors. The representative method of acquiring GCP is field survey to obtain accurate ground coordinates. However, it is difficult to find the GCP in the satellite image due to the quality of the image, land cover change, relief displacement, etc. By using image maps acquired from various sensors as reference data, it is possible to automate the collection of GCP through the image matching algorithm. In this study, the RPC of KOMPSAT-3A satellite image was corrected through the extracted matching point using the UAV (Unmanned Aerial Vehichle) imagery. We propose a pre-porocessing method for the extraction of matching points between the UAV imagery and KOMPSAT-3A satellite image. To this end, the characteristics of matching points extracted by independently applying the SURF (Speeded-Up Robust Features) and the phase correlation, which are representative feature-based matching method and area-based matching method, respectively, were compared. The RPC adjustment parameters were calculated using the matching points extracted through each algorithm. In order to verify the performance and usability of the proposed method, it was compared with the GCP-based RPC correction result. The GCP-based method showed an improvement of correction accuracy by 2.14 pixels for the sample and 5.43 pixelsfor the line compared to the vendor-provided RPC. In the proposed method using SURF and phase correlation methods, the accuracy of sample was improved by 0.83 pixels and 1.49 pixels, and that of line wasimproved by 4.81 pixels and 5.19 pixels, respectively, compared to the vendor-provided RPC. Through the experimental results, the proposed method using the UAV imagery presented the possibility as an alternative to the GCP-based method for the RPC correction.

• Korean Journal of Environmental Agriculture
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• v.37 no.3
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• pp.189-196
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• 2018

BACKGROUND: Water quality management of river requires quantification of pollutant loads and implementation of measures through monitoring study, but it requires labour and costs. Therefore, many researchers are performing nonpoint source pollution analysis using computer models. However, calibration of model parameters needs observed data. Nitrogen concentration in rainfall is one of the factors to be considered when estimating the pollutant loads through application of the nonpoint source pollution model, but the default value provided by the model is used when there are no observed data. Therefore, this study aims to provide the representative nitrogen concentration of the rainfall for the administrative district ensuring rational modeling and reliable results. METHODS AND RESULTS: In this study, rainfall monitoring data from June 2015 to December 2017 were used to determine the nitrogen concentration in rainfall for each administrative district. Range of the $NO_3{^-}$ and $NH_4{^+}$ concentrations were 0.41~6.05 mg/L, 0.39~2.27 mg/L, respectively, and T-N concentration was 0.80~7.71 mg/L. Furthermore, the national average of T-N concentration in this study was $2.84{\pm}1.42mg/L$, which was similar to the national average of T-N 3.03 mg/L presented by the Ministry of Environment in 2015. Therefore, the nitrogen concentrations suggested in this study can be considered to be resonable values. CONCLUSION: The nitrogen concentrations estimated in this study showed regional differences. Therefore, when estimating the pollutant loads through application of the nonpoint source pollution model, resonable parameter estimation of nitrogen concentration in rainfall is possible by reflecting the regional characteristics.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.198-221
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• 2021

After large-scale reforestation in the 1960s and 1970s, forests in Korea have gradually been aging. Net ecosystem CO₂ exchange of old-growth forests is theoretically near zero; however, it can be a CO₂ sink or source depending on the intervention of disturbance or management. In this study, we report the CO₂ budget dynamics of the Gwangneung deciduous old-growth forest (GDK) in Korea and examined the following two questions: (1) is the preserved GDK indeed CO₂ neutral as theoretically known? and (2) can we explain the dynamics of CO₂ budget by the common mechanisms reported in the literature? To answer, we analyzed the 15-year long CO₂ flux data measured by eddy covariance technique along with other biometeorological data at the KoFlux GDK site from 2006 to 2020. The results showed that (1) GDK switched back-and-forth between sink and source of CO₂ but averaged to be a week CO₂ source (and turning to a moderate CO₂ source for the recent five years) and (2) the interannual variability of solar radiation, growing season length, and leaf area index showed a positive correlation with that of gross primary production (GPP) (R²=0.32~0.45); whereas the interannual variability of both air and surface temperature was not significantly correlated with that of ecosystem respiration (RE). Furthermore, the machine learning-based model trained using the dataset of early monitoring period (first 10 years) failed to reproduce the observed interannual variations of GPP and RE for the recent five years. Biomass data analysis suggests that carbon emissions from coarse woody debris may have contributed partly to the conversion to a moderate CO₂ source. To properly understand and interpret the long-term CO₂ budget dynamics of GDK, new framework of analysis and modeling based on complex systems science is needed. Also, it is important to maintain the flux monitoring and data quality along with the monitoring of coarse woody debris and disturbances.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.19-45
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• 2008

This study is to empirically examine the primary dimensions of visual merchandising (VMD) of internet shopping mall, namely store design, merchandise, and merchandising cues, to be a attractive virtual store to the shoppers. The authors reviewed the literature related to the major components of VMD from the perspective of the AIDA model, which has been mainly applied to the offline store settings. The major purposes of the study are as follows; first, tries to derive the variables related with the components of visual merchandising through reviewing the existing literatures, establish the hypotheses, and test it empirically. Second, examines the relationships between the components of VMD and the attitude toward the VMD, however, putting more emphasis on finding out the component structure of the VMD. VMD needs to be examined with the perspective that an online shopping mall is a virtual self-service or clerkless store, which could reduce the number of employees, help the shoppers search, evaluate and purchase for themselves, and to be explored in terms of the in-store persuasion processes of customers. This study reviewed the literatures related to store design, merchandise, and merchandising cues which might be relevant to the store, product, and promotion respectively. VMD is a total communication tool, and AIDA model could explain the in-store consumer behavior of online shopping. Store design has to do with triggering a consumer attention to the online mall, merchandise with a product related interest, and merchandising cues with promotions such as recommendation and links that induce the desire to pruchase. These three steps might be seen as the processes for purchase actions. The theoretical rationale for the relationship between VMD and AIDA could be found in Tyagi(2005) that the three steps of consumer-oriented merchandising are a store, a product assortment, and placement, in Omar(1999) that three types of interior display are a architectural design display, commodity display, and point-of-sales(POS) display, and in Davies and Ward(2005) that the retail store interior image is related to an atmosphere, merchandise, and in-store promotion. Lee et al(2000) suggested as the web merchandising components a merchandising cues, a shopping metaphor which is an assistant tool for search, a store design, a layout(web design), and a product assortment. The store design which includes differentiation, simplicity and navigation is supposed to be related to the attention to the virtual store. Second, the merchandise dimensions comprising product assortments, visual information and product reputation have to do with the interest in the product offerings. Finally, the merchandising cues that refer to merchandiser(MD)'s recommendation of products and providing the hyperlinks to relevant goods for the shopper is concerned with attempt to induce the desire to purchase. The questionnaire survey was carried out to collect the data about the consumers who would shop at internet shopping malls frequently. To select the subject malls, the mall ranking data announced by a mall rating agency was used to differentiate the most popular and least popular five mall each. The subjects was instructed to answer the questions after navigating the designated mall for five minutes. The 300 questionnaire was distributed to the consumers, 166 samples were used in the final analysis. The empirical testing focused on identifying and confirming the dimensionality of VMD and its subdimensions using a structural equation modeling method. The confirmatory factor analysis for the endogeneous and exogeneous variables was carried out in four parts. The second-order factor analysis was done for a store design, a merchandise, and a merchandising cues, and first-order confirmatory factor analysis for the attitude toward the VMD. The model test results shows that the chi-square value of structural equation is 144.39(d.f 49), significant at 0.01 level which means the proposed model was rejected. But, judging from the ratio of chi-square value vs. degree of freedom, the ratio was 2.94 which smaller than an acceptable level of 3.0, RMR is 0.087 which is higher than a generally acceptable level of 0.08. GFI and AGFI is turned out to be 0.90 and 0.84 respectively. Both NFI and NNFI is 0.94, and CFI 0.95. The major test results are as follows; first, the second-order factor analysis and structural equational modeling reveals that the differentiation, simplicity and ease of identifying current status of the transaction are confirmed to be subdimensions of store design and to be a significant predictors of the dependent variable. This result implies that when designing an online shopping mall, it is necessary to differentiate visually from other malls to improve the effectiveness of the communications of store design. That is, the differentiated store design raise the contrast stimulus to sensory organs to promote the memory of the store and to have a favorable attitude toward the VMD of a store. The results that navigation which means the easiness of identifying current status of shopping affects the attitude to VMD could be interpreted that the navigating processes via the hyperlinks which is characteristics of an internet shopping is a complex and cognitive process and shoppers are likely to lack the sense of overall structure of the store. Consequently, shoppers are likely to be alost amid shopping not knowing where to go. The orientation tool enhance the accessibility of information to raise the perceptive power about the store environment.(Titus & Everett 1995) Second, the primary dimension of merchandise and its subdimensions was confirmed to be unidimensional respectively, have a construct validity, and nomological validity which the VMD dimensions supposed to have a positive correlation with the dependent variable. The subdimensions of product assortment, brand fame and information provision proved to have a positive effect on the attitude toward the VMD. It could be interpreted that the more plentiful the product and brand assortment of the mall is, the more likely the shoppers to favor it. Brand fame and information provision as well affect the VMD attitude, which means that the more famous the brand, the more likely the shoppers would trust and feel familiar with the mall, and the plentifully and visually presented information could have the shopper have a favorable attitude toward the store VMD. Third, it turned out to be that merchandising cue of product recommendation and hyperlinks affect the VMD attitude. This could be interpreted that recommended products could reduce the uncertainty related with the purchase decision, and the hyperlinks to relevant products would help the shopper save the cognitive effort exerted into the information search and gathering, which could lead to a favorable attitude to the VMD. This study tried to sheds some new light on the VMD of online store by reviewing the variables mentioned to be relevant with offline VMD in the existing literatures, and tried to link the VMD components from the perspective of AIDA model. The effect size of the VMD dimensions on the attitude was in the order of the merchandise, the store design and the merchandising cues.It is said that an internet has an unlimited place for display, however, the virtual store is not unlimited since the consumer has a limited amount of cognitive ability to process the external information and internal memory. Particularly, the shoppers are likely to face some difficulties in decision making on account of too many alternative and information overloads. Therefore, the internet shopping mall manager should take into consideration the cost of information search on the part of the consumer, to establish the optimal product placements and search routes. An efficient store composition would be possible by reducing the psychological burdens and cognitive efforts exerted to information search and alternatives evaluation. The store image is in most part determined by the product category and its brand it deals in. The results of this study support this proposition that the merchandise is most important to the VMD attitude than other components, the manager is required to take a strategic approach to VMD. The internet users are getting more accustomed and more knowledgeable about the internet media and more likely to accept the internet as a shopping channel as the period of time during which they use the internet to shop become longer. The web merchandiser should be aware that the product introduction using a moving pictures and a bulletin board become more important in order to present the interactive product information visually and communicate with customers more actively, therefore leading to making the quantity and quality of product information more rich.

• Journal of the East Asian Society of Dietary Life
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• v.21 no.6
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• pp.934-947
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• 2011

The purpose of this study is to analyze products for good taste and convenience, which become an engine to constantly create customers. In addition, this study is aimed at investigating the relationship between the selective attributes of Home Meal Replacement, the perceived utilitarian value, and the repurchase intention, and drawing new suggestions on the Home Meal Replacement market from a new marketing perspective. Based on a total of 215 samples, this study reviewed the reliability and fitness of the research model and verified a total of 5 hypothesized using the Amos program. The result of study modeling was GFI=0.905, AGFI=0.849, NFI=0.889, CFI=0.945, and RMR=0.0.092 at the level of $x^2$=230.22 (df=126, p<0.001). First, the food quality (${\beta}$=0.221), convenience (${\beta}$=0.334), packing (${\beta}$=0.278), and employee service (${\beta}$=0.204) of home meal replacement consideration attributes had a positive (+) influence on perceived utilitarian value. Second, perceived utilitarian value (${\beta}$=0.584) had a positive (+) influence on repurchase intention. The factors to differentiate one company from other competitors in terms of the utilitarian value are the quality of food, convenience, wrapping, and services by employees. This study has illustrated the need to focus on the development of a premium menu to compete with other companies and to continue to research and develop nutritious foods that are easy to cook. Moreover, the key factors to have a distinct and constant competitive edge over other companies are the alleviation of consumer anxiety over wrapping container materials, the development of more designs, and the accumulation of service know-how. Therefore, it is necessary for a company to strongly develop the key factors based on its resources as a core capability.