• Korean Journal of Culture and Social Issue
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• v.28 no.4
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• pp.691-715
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• 2022

In this study, we investigated the relationship between Finsta use and perceived online social support, self-monitoring, and subjective well-being. Furthermore, we investigated whether the number of Instagram accounts mediates the relationship between self-monitoring and perceived online social support. For this reason, To this end, we conducted an online survey of 396 adults in their 20s. Results indicated that the number of Instagram accounts showed a positive correlation with perceived online social support and self-monitoring, but did not show a significant correlation with subjective well-being. Next, it was found that the higher the level of self-monitoring, the higher the probability of using of Finsta. In addition, the number of Instagram accounts was found to partially mediate the relationship between self-monitoring and perceived online social support. In other words, the higher the self-monitoring was associated with, , the more Instagram accounts were, and many Instagram accounts increased the level of perceived online social support. For the first time in Korea, this study confirmed the relationship between Finsta use and perceived online social support, self-monitoring, and subjective well-being., Also, this study was meaningful because itand explored whether self-monitoring leads to perceived online social support through the number of Instagram accounts. In addition, this studyit has social meaning in that it sheds light on how online interactions are connected to the real world.

• Smart Structures and Systems
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• v.14 no.2
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• pp.129-144
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• 2014

In this paper, a fuzzy inference system and an analytical hierarchy process-based online evaluation technique is developed to monitor the condition of the 32-km Donghai Bridge in Shanghai. The system has 478 sensors distributed along eight segments selected from the whole bridge. An online evaluation subsystem is realized, which uses raw data and extracted features or indices to give a set of hierarchically organized condition evaluations. The thresholds of each index were set to an initial value obtained from a structure damage and performance evolution analysis of the bridge. After one year of baseline monitoring, the initial threshold system was updated from the collected data. The results show that the techniques described are valid and reliable. The online method fulfills long-term infrastructure health monitoring requirements for the Donghai Bridge.

• KSBB Journal
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• v.28 no.1
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• pp.24-30
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• 2013

Dissolved oxygen, pH and cell concentration have been online monitored in cultivation processes with Escherichia coli by using a $MABOOMS^{TM}$ (microplate-based bioreactor with optical online monitoring systems). Fluorescent sensing membranes containing Ru ${(dpp)_3}^{2+}$ or HPTS were prepared with GA sol-gel matrix and coated into a well of a 24-well microplate. Fluorescence intensity was measured and correlated to the dissolved oxygen or pH. Cell concentrations were also online monitored by measuring optical reflectance at 650 nm. A well of a 24-well microplate could also be divided into 4 parts, each of which was coated with fluorescent sensing membranes for the detection of dissolved oxygen or pH. The 24-well microplate coated with fluorescent sensing membranes or a 4-divided sensing membrane. was used to online monitor the dissolved oxygen, pH and cell concentration during E. coli cultivations. The online monitoring results showed the characteristics of cell growth in cultivation processes very well.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.85-96
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• 2015

Despite the growth of body-related industry has generated considerable interest in this topic among both academics and practitioners, there has been lack of studies that explore body esteem toward online fashion products leads to purchase intentions, which self-monitoring moderates the relationship between body esteem toward online fashion products and purchase intentions. To fill this gap, this study aim to propose a research model where body esteem influences on the purchase intentions, with self-monitoring as a moderator. In order to test hypotheses, response from 172 consumers were achieved, and the proposed model was estimated by using hierarchical moderated regression analysis. The empirical results showed that body esteem negatively related to purchase intentions toward online fashion products. Additionally, this study indicated that the moderating effects of self-monitoring exist between body esteem and purchase intentions toward online fashion products, thereby implying the importance of contingent role of self-monitoring in managing online channels.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.526-536
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• 2021

This study looked at what factors lead to continuous participatory intention of online childrearing community. Trust, reciprocity and perceived security from the perspectives of community attributes and reputation motivation, information motivation, enjoyment motivation and self-monitoring from the users' perspectives were conceived as determinants that might have influences on continuous participatory intention of online childrearing community. It were also empirically tested whether they affect continuous participatory intention of online childrearing community. The moderating effect of self-monitoring was examined, too. In order to collect data, online questionnaires were conducted to women whose ages were 20-49 years old and joined online childrearing community. Their responses were analyzed with a regression analysis. The findings showed that trust, reciprocity and information motivation have influences on continuous participatory intention of online childrearing community. The moderating effect of self-monitoring between reciprocity and continuous participatory intention was also found.

• Journal of Digital Convergence
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• v.16 no.5
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• pp.207-211
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• 2018

TThis research paper discusses the results of an article on the effects of moderating role of self-monitoring on response to the two different types of online advertising appeals. It was hypothesized that low self-monitors show more positive attitude towards brand when exposing advertisements with product quality-based online advertising than high self-monitors, whereas high self-monitors show more positive attitude towards brand when exposing advertisements with image-based online advertising than low self-monitors. Through an experimental design involving product quality and image-based online advertising, this article demonstrates that the role of self-monitoring in online advertising effects is similar to traditional advertising studies. Based on the results of the study, practical and theoretical suggestions are interpreted in relation to online advertising creative messages and strategies.

• Structural Monitoring and Maintenance
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• v.7 no.4
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• pp.345-365
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• 2020

At present, many machine leaning and data mining methods are used for analyzing and predicting structural response characteristics. However, the platform that combines big data analysis methods with online and offline analysis modules has not been used in actual projects. This work is dedicated to developing a multifunctional Hadoop-Spark big data platform for bridges to monitor and evaluate the serviceability based on structural health monitoring system. It realizes rapid processing, analysis and storage of collected health monitoring data. The platform contains offline computing and online analysis modules, using Hadoop-Spark environment. Hadoop provides the overall framework and storage subsystem for big data platform, while Spark is used for online computing. Finally, the big data Hadoop-Spark platform computational performance is verified through several actual analysis tasks. Experiments show the Hadoop-Spark big data platform has good fault tolerance, scalability and online analysis performance. It can meet the daily analysis requirements of 5s/time for one bridge and 40s/time for 100 bridges.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.842-850
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• 2021

Real Time Simulation (RTS) has long been used in the nuclear power industry for operator training and engineering purposes. And, Online Simulation (OLS) is based on RTS and with connection to the plant information system to acquire the measurement data in real time for calibrating the simulation models and following plant operation, for the purposes of analyzing plant events and providing indicative signs of malfunctioning. An OLS system has been developed to support PWR operations for CPR1000 plants. The OLS system provides graphical user interface (GUI) for operators to monitor critical plant operations for preventing faulty operation or analyzing plant events. Functionalities of the OLS system are depicted through the maneuvering of the GUI for various OLS functional modules in the system.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4751-4758
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• 2022

Two-phase flow may almost exist in every branch of the energy industry. For the corresponding engineering design, it is very essential and crucial to monitor flow patterns and their transitions accurately. With the high-speed development and success of deep learning based on convolutional neural network (CNN), the study of flow pattern identification recently almost focused on this methodology. Additionally, the photographing technique has attractive implementation features as well, since it is normally considerably less expensive than other techniques. The development of such a two-phase flow pattern online monitoring system is the objective of this work, which seldom studied before. The ongoing preliminary engineering design (including hardware and software) of the system are introduced. The flow pattern identification method based on CNNs and transfer learning was discussed in detail. Several potential CNN candidates such as ALexNet, VggNet16 and ResNets were introduced and compared with each other based on a flow pattern dataset. According to the results, ResNet50 is the most promising CNN network for the system owing to its high precision, fast classification and strong robustness. This work can be a reference for the online monitoring system design in the energy system.

• YAKHAK HOEJI
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• v.60 no.2
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• pp.85-91
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• 2016

Drying of granules for tablet formulation is one of the important unit operations. The loss on drying method is traditionally used for this purpose. However, it is a time-consuming method, requiring at least 1 h. Moreover, it is ineffective in monitoring the moisture content of granules during the drying process. In this study, online real-time monitoring of moisture content during the drying process was successfully performed using near-infrared (NIR) spectroscopy. NIR spectra were collected during 15 different drying batches for developing a reliable NIR spectroscopic method. Such a large number of batches were used to develop a more robust partial least squares (PLS) model. NIR spectra collected from 12 batches were used for developing the model that was validated by predicting the moisture content of the samples in the remaining 3 batches. The standard errors of predictions (SEPs) in the measurement of batch 1, batch 2, and batch 3 were 0.52%, 0.57%, and 0.56%, respectively. The online NIR spectroscopic method developed in this study was reliable and accurate in monitoring the moisture content during the drying process.