• Journal of the Korean Society for Library and Information Science
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• v.33 no.1
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• pp.67-86
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• 1999

It needs to be considered that citing is net a static process but a dynamic process which is to produce to reproduce and to distribute knowledge by the interaction between societies surrounding the citer. This study begins by briefly acknowledging that citation is a universal practice in terms of establishing citer's own basis of research on the basis of the relation to previous studies and persuadeing potential citer to cite his/her research product. This study, however, is a preliminary attempt to examine the premise that although citing is a unversal practice. but citer motivations can be influenced by various citation environmental contexts surrounding the citer. This study presented general citation motivations derived from previous studies: (1) substantial motivations - conceptional and methodological citations 2) persuasive motivations - positive, applied, and negative citations, (3) perfunctory motivations - perfunctory and bibliographic citations, and (4) social relation motivations - personal connections and knowledge familiarity citations. In addition, this study identified citation environment factors affecting these citation motivations: (1) citer and documentation factor, (2) social and cultural environment, (3) information environment, and (4) international knowledge system environment. Each citation environment factor presented should be interpreted not as a separate factor, but rather as a close interrelation among these environment factors, Finally, the model of the citation environment factors developed in this study was discussed in the aspects of the relationship between citation motivations and their citation environment factors. This study suggested that further research should be conducted in order to examine these relationships more empirically and citation should be considered as a social product reflecting the interaction between citer and various citation environments.

• Journal of Distribution Science
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• v.17 no.3
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• pp.85-95
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• 2019

Purpose - The existing marketing studies using Social Network Analysis have assumed that network structure variables are time-invariant. However, a node's network position can fluctuate considerably over time and the node's network structure can be changed dynamically. Hence, if such a dynamic structural network characteristics are not specified for virtual goods purchase model, estimated parameters can be biased. In this paper, by comparing a time-invariant network structure specification model(base model) and time-varying network specification model(proposed model), the authors intend to prove whether the proposed model is superior to the base model. In addition, the authors also intend to investigate whether coefficients of network structure variables are random over time. Research design, data, and methodology - The data of this study are obtained from a Korean social network provider. The authors construct a monthly panel data by calculating the raw data. To fit the panel data, the authors derive random effects panel tobit model and multi-level mixed effects model. Results - First, the proposed model is better than that of the base model in terms of performance. Second, except for constraint, multi-level mixed effects models with random coefficient of every network structure variable(in-degree, out-degree, in-closeness centrality, out-closeness centrality, clustering coefficient) perform better than not random coefficient specification model. Conclusion - The size and importance of virtual goods market has been dramatically increasing. Notwithstanding such a strategic importance of virtual goods, there is little research on social influential factors which impact the intention of virtual good purchase. Even studies which investigated social influence factors have assumed that social network structure variables are time-invariant. However, the authors show that network structure variables are time-variant and coefficients of network structure variables are random over time. Thus, virtual goods purchase model with dynamic network structure variables performs better than that with static network structure model. Hence, if marketing practitioners intend to use social influences to sell virtual goods in social media, they had better consider time-varying social influences of network members. In addition, this study can be also differentiated from other related researches using survey data in that this study deals with actual field data.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.32 no.2
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• pp.204-210
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• 1999

The present studies were conducted to evaluate the effects of activin-A on gonadotropins (GTHs) release in testosterone-treated immature rainbow trout Oncorhpynchus mykiss. The administration of testosterone elevated pituitary level of GTH II but not of GTH I. In this study using primary cultures of dispersed pituitary cells in static incubation, dose-dependent increases in GTH II release was observed in the activin-treated group at day 3 of incubation (long-term incubation), but not at day 1 of incubation (short-term incubation). Dopamine, a potent inhibitor of gonadotropin-releasing hormone (GnRH)-stimulated GTH II release in rainbow trout, was only partially effective in decreasing actvin-induced GTH II release. Furthermore, salmon GnRH (sGnRH)-stimulated GTH II release was not potentiated by the pretreatment with activin. However, the control mechanisms of GTH I release by activin and other hormones were not observed in the all tested experiments. The results of these studies support the contention that in contrast with the usual stimulatory effects of activin on GTH release in mammals, activin exerts long-term stimulatory actions on GTH II release in rainbow trout. The control mechanism of GTH I release, however, is a question that remains to be elucidated.

• The Journal of Engineering Geology
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• v.13 no.4
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• pp.419-428
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• 2003

In order to evaluate groundwater movement and the infiltration of contaminants, such as petroleum products, the determination of porosity and effective porosity is very important. Porosity and effective porosity are important physical parameters that determine the transfer and movement of water and solutes in porous media. Various methods of determining these parameters have been developed, with varying degrees of accuracy and applicability. Most of the existing methods produce static results. They do not produce instantaneous and real time of porosity and effective porosity in a porous media. In this study, we used a new permittivity method called Frequency Domain Reflectometry with Vector analyzer (FDR-V) to determine the porosity and effective porosity of some sand samples in the laboratory. The advantage of the FDR-V method is that it instantaneously determines the temporal variation of dielectric constants of porous media. Then, the porosity and the effective porosity of porous media are computed using well established empirical equations. Results obtained from the FDR-V method compared favorably with results from other permittivity methods such as gravimetric, injection and replacement tests. The ratio of effective porosity to porosity was 85 - 92 %, when FDR-V was used. This value compared favourably with 90 %, which has been usually quoted in previous studies. Considering the convenience and its applicability, the EDR-V permittivity holds a great potential in porous media and contaminant transport studies.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.1
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• pp.31-41
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• 2019

Volatile organic compounds(VOCs) are toxic carcinogenic compounds found in wastewater. VOCs require rapid removal because they are easily volatilized during wastewater treatment. Electrochemical advanced oxidation processes(EAOPs) are considered efficient for VOC removal, based on their fast and versatile anodic electrochemical oxidation of pollutants. Many studies have reported the efficiency of removal of various types of pollutants using different anodes, but few studies have examined volatilization of VOCs during EAOPs. This study examined the removal efficiency for VOCs (chloroform, benzene, trichloroethylene and toluene) by oxidization and volatilization under a static stirred, aerated condition and an EAOP to compare the volatility of each compound. The removal efficiency of the optimum anode was determined by comparing the smallest volatilization ratio and the largest oxidization ratio for four different dimensionally stable anodes(DSA): Pt/Ti, $IrO_2/Ti$, $IrO_2/Ti$, and $IrO_2-Ru-Pd/Ti$. EAOP was operated under same current density ($25mA/cm^2$) and electrolyte concentration (0.05 M, as NaCl). The high volatility of the VOCs resulted in removal of more than 90% within 30 min under aerated conditions. For EAOP, the $IrO_2-Ru/Ti$ anode exhibited the highest VOC removal efficiency, at over 98% in 1 h, and the lowest VOC volatilization (less than 5%). Chloroform was the most recalcitrant VOC due to its high volatility and chemical stability, but it was oxidized 99.2% by $IrO_2-Ru/Ti$, 90.2% by $IrO_2-Ru-Pd/Ti$, 78% by $IrO_2/Ti$, and 75.4% by Pt/Ti anodes The oxidation and volatilization ratios of the VOCs indicate that the $IrO_2-Ru/Ti$ anode has superior electrochemical properties for VOC treatment due to its rapid oxidation process and its prevention of bubbling and volatilization of VOCs.

• Korean Journal of Environmental Agriculture
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• v.39 no.4
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• pp.297-304
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• 2020

BACKGROUND: Emission of nitrous oxide (N2O) from the soil is expected to depend on the types of nitrogen fertilizer used. Biochar has recently been proposed as a potential mitigation of climate change by reducing the N2O emission. Although laboratory studies reported that biochar applications could reduce N2O emission, the number of field-based studies is still limited. Therefore, a field experiment was conducted to investigate the effect of biochar on N2O emission when different nitrogen fertilizers were applied in corn cultivated field. METHODS AND RESULTS: The field experiment consisted of six treatments: urea fertilizer without biochar (U), ammonium sulfate fertilizer without biochar (A), oil cake fertilizer without biochar (O), urea fertilizer with biochar (U+B), ammonium sulfate fertilizer with biochar (A+B), and oil cake fertilizer with biochar (O+B). Biochar was applied at a rate of 10 t/ha. Greenhouse gas fluxes were measured during growing seasons using static vented chambers. The cumulative N2O emissions were 0.99 kg/ha in the U, 1.23 kg/ha in the A, 3.25 kg/ha in the O, 1.19 kg/ha in the U+B, 0.86 kg/ha in the A+B, and 1.55 kg/ha in the O+B. CONCLUSION: It was found that N2O emission was related to application of both nitrogen fertilizer type and biochar. In particular, the N2O reduction effect was the highest in the corn field incorporated with biochar when oil cake was applied to the soil.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.112-125
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• 2021

Marine spatial planning(MSP) designates the marine as nine kinds of use zones for the systematic and rational management of marine spaces. One of them is the fishery protection zone, which is necessary for the sustainable production of fishery products, including the protection and fosterage of fishing activities. This study intends to quantitatively identify the fishing activity space, one of the elements necessary for the designation of fisheries protection zones, by mapping of fishery activities using V-Pass data and deriving the fishery activity concentrated zone. To this end, pre-processing of V-Pass data was performed, such as constructing a dataset that combines static and dynamic information, calculating the speed of fishing vessels, extracting fishing activity points, and removing data in non-fishing activity zone. Finally, using the selected V-Pass point data, a fishery activity map was made by kernel density estimation, and the concentrated space of fishery activity was analyzed. In addition, it was confirmed that there is a difference in the spatial distribution of fishing activities according to the type of fishing vessel and the season. The pre-processing technique of large volume V-Pass data and the mapping method of fishing activities performed through this study are expected to contribute to the study of spatial characteristics evaluation of fishing activities in the future.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.9-16
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• 2020

A CFRP sheet has been applied as a structural reinforcement in the field, and various studies are conducted to evaluate the effect of CFRP sheets on reinforced concrete. Although many experiments were performed from previous studies, there are still limitations to analyze structural behaviors with various parameters in experiments directly. This study shows the FEA on structural behaviors of RC beams reinforced with CFRP sheets using ABAQUS software. To simulate debonding failure of CFRP sheets which is a major failure mode of RC beam with CFRP sheets, a cohesive element was applied between the bottom surface of RC beam and CFRP sheets. Both quasi-static method and 2-D symmetric FE model technique were performed to solve nonlinear problems. Results obtained from the FE models show good agreements with experimental results. It was found that reinforcement level of CFRP sheets is closely related to structural behavior of reinforced concrete including maximum strength, initial stiffness and deflection at failure. Also, as over-reinforcement of CFRP sheets could give rise to the brittle failure of RCstructure using CFRP sheets, an appropriate measure should be required when installing CFRP sheets in the structure.

• Knowledge Management Research
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• v.22 no.4
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• pp.237-260
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• 2021

This study aims to make suggestions for more effective budget utilization and R&D project investment through verification of the efficiency of research results for the government's R&D projects. Efficiency was analyzed using Data Envelope Analysis(DEA) and 'Malmquist Index analysis' for the research results of convergence research projects organized by the National Science and Technology Research Association. The analysis targets were convergence research projects organized by the National Science and Technology Research Association and general entrusted research projects by government-funded research institutes, and dynamic analysis was conducted using DEA and Malmquist Index analysis. As a result of the analysis, the convergence research project showed high efficiency from the static perspective of DEA. On the other hand, from a dynamic perspective through the Malmquist Index analysis method, the efficiency of the general consignment project gradually declined, while the efficiency of the convergence research project improved every year. This suggests that convergence studies have higher results than general studies. Through the results of this study, we intend to present objective standards for performance evaluation of government R&D investment and provide objective implications for rational investment policies and research project planning of research personnel and research funds to improve efficiency for government-funded research institutes.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.445-454
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• 2023

Recently, various fault diagnosis studies are being conducted utilizing data from collaborative robots. Existing studies performing fault diagnosis on collaborative robots use static data collected based on the assumed operation of predefined devices. Therefore, the fault diagnosis model has a limitation of increasing dependency on the learned data patterns. Additionally, there is a limitation in that a diagnosis reflecting the characteristics of collaborative robots operating with multiple joints could not be conducted due to experiments using a single motor. This paper proposes an LSTM diagnostic model that can overcome these two limitations. The proposed method selects representative normal patterns using the correlation analysis of vibration and current data in single-axis and multi-axis work environments, and generates residual patterns through differences from the normal representative patterns. An LSTM model that can perform gear wear diagnosis for each axis is created using the generated residual patterns as inputs. This fault diagnosis model can not only reduce the dependence on the model's learning data patterns through representative patterns for each operation, but also diagnose faults occurring during multi-axis operation. Finally, reflecting both internal and external data characteristics, the fault diagnosis performance was improved, showing a high diagnostic performance of 98.57%.