• Korean Journal of Materials Research
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• v.25 no.3
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• pp.119-124
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• 2015

This paper investigates the change of the percolation threshold in the carbon powder-filled polystyrene matrix composites based on the experimental results of changes in the resistivity and relative permittivity of the carbon powder filling, the electric field dependence of the current, and the critical exponent of conductivity. In this research, the percolation behavior, the critical exponent of resistivity, and electrical conduction mechanism of the carbon powder-filled polystyrene matrix composites are discussed based on a study of the overall change in the resistivity. It was found that the formation of infinite clusters is interrupted by a tunneling gap in the volume fraction of the carbon powder filling, where the change in the resistivity is extremely large. In addition, it was found that the critical exponent of conductivity for the universal law of conductivity is satisfied if the percolation threshold is estimated at the volume fraction of carbon powder where non-ohmic current behavior becomes ohmic. It was considered that the mechanism for changing the gaps between the carbon powder aggregates into ohmic contacts is identical to that of the connecting conducting phases above the percolation threshold in a random resister network system. The electric field dependence is discussed with a tunneling mechanism. It is concluded that the percolation threshold should be defined at this volume fraction (the second transition of resistivity for the carbon powder-filled polystyrene matrix composites) of carbon powder.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2222-2240
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• 2023

Brand fandom refers to a collection of consumers with strong emotions toward a brand. Studying the dynamics of brand fandom can help brands understand which services or strategies influence their consumers to become a part of brand fandom. However, existing literature on fandom in the last three decades has mainly used qualitative methods, and there is still a lack of research on fandom using quantitative methods. Specifically, previous studies lack a framework for locating fandoms from online textual data and analyzing their dynamics. This study proposes a framework for exploring brand fandom dynamics based on online textual data. This framework consists of four phases based on the design thinking model: Preparing Data, Defining Fandom Categories, Generating Fandom Dynamics, and Analyzing Fandom Dynamics. This framework uses techniques such as social network analysis and process mining, combined with brand personality theory. We demonstrate the applicability of this framework using case studies of two Korean home appliance brands. The dataset contains 14,593 posts by consumers in 374 online communities. The results show that the proposed framework can analyze brand fandom dynamics using textual customer data. Our study contributes to the interdisciplinary research at the intersection of data-driven service design and consumer culture quantification.

• Journal of Preventive Medicine and Public Health
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• v.56 no.4
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• pp.327-337
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• 2023

Objectives: Considering the importance of social determinants of health (SDHs) in promoting the health of residents of informal settlements and their diversity, abundance, and breadth, this study aimed to identify, measure, and rank SDHs for health promotion interventions targeting informal settlement residents in a metropolitan area in Iran. Methods: Using a hybrid method, this study was conducted in 3 phases from 2019 to 2020. SDHs were identified by reviewing studies and using the Delphi method. To examine the SDHs among informal settlement residents, a cross-sectional analysis was conducted using researcher-made questionnaires. Multilayer perceptron analysis using an artificial neural network was used to rank the SDHs by priority. Results: Of the 96 determinants identified in the first phase of the study, 43 were examined, and 15 were identified as high-priority SDHs for use in health-promotion interventions for informal settlement residents in the study area. They included individual health literacy, nutrition, occupational factors, housing-related factors, and access to public resources. Conclusions: Since identifying and addressing SDHs could improve health justice and mitigate the poor health status of settlement residents, ranking these determinants by priority using artificial intelligence will enable policymakers to improve the health of settlement residents through interventions targeting the most important SDHs.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.67.2-67.2
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• 2019

We present the results of KVN and ALMA observations toward WX Psc (IRC+10011) which is a long-period variable OH/IR star. The SiO masers of v=1 and v=2, J=5-4, and the SiO thermal emission of v=0, J=5-4 were observed together with H2O v2=1 (232.6 GHz) and continuum emission at ALMA Band 6 in October 2017 (Cycle 5). This observation aims to investigate the physical association between the inner and outer parts of the circumstellar envelope (CSE) swept by the stellar winds, which is very crucial to understand the asymmetric outward motions developed during the evolutionary phases from the asymptotic giant branch (AGB) stars to the planetary nebulae (PNe). The strong SiO maser features and thermal emissions are detected together with the continuum emission in ALMA observation, which imply the elongated morphology of the CSE of WX Psc. While the spatial resolution of about 20 mas in ALMA observation cannot clearly resolve the detailed characteristics of the inner part of the CSE, the Korean VLBI Network (KVN) observations show the spatial distributions of the v=1 J=1-0, J=2-1, J=3-2 SiO masers emitted from the inner regions of CSE, which are the complementary to the ALMA results. Therefore, we expect these results reveal how the bipolar features of the 22 GHz H2O maser are connected to the innermost region of CSE through the dust condensation region, which is closely related to the enormous mass ejection of the evolved stars.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.975-983
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• 2022

This paper presents an innovative way of integrating scheduling and project controls with the environmental impact of a construction project to track, monitor, and manage environmental emissions at the activity level. As a starting point, scheduling and project controls help monitor the status of a project to provide an assessment of the duration and sequence of activities. Additionally, project schedules can also reflect resource allocation and costs associated with various phases of a construction project. Owners, contractors and construction managers closely monitor tasks or activities on the critical path(s) and/or longest path(s) calculated through network based scheduling techniques. However, existing industry practices do not take into account environmental impact associated with each activity during the life cycle of a project. Although the environmental impact of a project may be tracked in various ways, that tracking is not tied to the project schedule and, as such, generally is not updated when schedules are revised. In this research, a Cradle to Gate approach is used to estimate environmental emissions associated with each activity of a sample project schedule. The research group has also investigated the potential determination of scenarios of lowest environmental emissions, just as project managers currently determine scenarios with lowest cost or time. This methodology can be scaled up for future work to develop a library of unit emissions associated with commonly used construction materials and equipment. This will be helpful for project owners, contractors, and construction managers to monitor, manage, and reduce the carbon footprint associated with various projects.

• IMMUNE NETWORK
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• v.20 no.3
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• pp.23.1-23.20
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• 2020

Sepsis is conceptually defined as life-threatening organ dysfunction that is caused by a dysregulated host response to infection. Although there has been significant advancement in recent decades in defining and understanding sepsis pathology, clinical management of sepsis is challenging due to difficulties in diagnosis, a lack of reliable prognostic biomarkers, and treatment options that are largely limited to antibiotic therapy and fundamental supportive measures. The lack of reliable diagnostic and prognostic tests makes it difficult to triage patients who are in need of more urgent care. Furthermore, while the acute inpatient treatment of sepsis warrants ongoing attention and investigation, efforts must also be directed toward longer term survival and outcomes. Sepsis survivors experience incomplete recovery, with long-term health impairments that may require both cognitive and physical treatment and rehabilitation. This review summarizes recent advances in sepsis prognosis research and discusses progress made in elucidating the underlying causes of prolonged health deficits experienced by patients surviving the early phases of sepsis.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.667-671
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• 2006

Co-Authorship analysis is a kind of bibliometric analysis. and a well established tool for character of knowledge network in some technical fields. If more than two authors co-author an article, there is a relation of knowledge. So This study aims at discovering the trends and phases of OLED technology using co-authorship analysis, a kind of bibliographic analysis. The Science Citation Index Expanded(SCIE) database was used to search for the number of times paired Korean articles were co-authored in OLED field.

• Journal of Biomedical Engineering Research
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• v.29 no.6
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• pp.502-511
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• 2008

This study was designed to develop a new algorithm to extract the voluntary EMG and the evoked EMG from a mixed EMG generated when the muscle is stimulated both voluntarily and by electrical stimulation in the FES system. The proposed parallel filter algorithm consists of three phases: (1) Fourier transform of the mixed EMG, (2) multiplication of the transformed signal to two frequency functions, and (3) inverse Fourier transform. Four incomplete spinal cord injured patients participated in the experiments to evaluate the algorithm by measuring the knee extensor torque and the EMG signals from the quadriceps. Two functions of the algorithms were evaluated: (1) extraction of the evoked EMG and (2) the voluntary EMG from the mixed EMG. The results showed that the algorithm enabled us to separate the two EMG components in real time from the mixed EMG. The algorithm can and will be used for estimating the voluntary torque and the evoked torque independently through an artificial neural network based on the two EMG components, and also for generating a trigger signal to control the on/off time of the FES system.

• Environmental Engineering Research
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• v.22 no.3
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• pp.302-311
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• 2017

Nowadays, with the burgeoning development of economy, $CO_2$ emissions increase rapidly in China. It has become a common concern to seek effective methods to forecast $CO_2$ emissions and put forward the targeted reduction measures. This paper proposes a novel hybrid model combined principal component analysis (PCA) with regularized extreme learning machine (RELM) to make $CO_2$ emissions prediction based on the data from 1978 to 2014 in China. First eleven variables are selected on the basis of Pearson coefficient test. Partial autocorrelation function (PACF) is utilized to determine the lag phases of historical $CO_2$ emissions so as to improve the rationality of input selection. Then PCA is employed to reduce the dimensionality of the influential factors. Finally RELM is applied to forecast $CO_2$ emissions. According to the modeling results, the proposed model outperforms a single RELM model, extreme learning machine (ELM), back propagation neural network (BPNN), GM(1,1) and Logistic model in terms of errors. Moreover, it can be clearly seen that ELM-based approaches save more computing time than BPNN. Therefore the developed model is a promising technique in terms of forecasting accuracy and computing efficiency for $CO_2$ emission prediction.

• IMMUNE NETWORK
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• v.6 no.1
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• pp.1-5
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• 2006

Background: B cell subset has been divided into B-1 cells and B-2 cells. B-1 cells are found most prominently in the peritoneal cavity, as well as constituting a small pro portion of splenic B cells and they are larger and less dense than B-2 cells in morphology. This study was designed to compare the differences in their proliferation and differentiation between B-1 and B-2 cell. Methods: We obtained sorted B-1 cells from peritoneal fluid and B-2 cells from spleens of mice. Secreted IgM was measured by enzyme-linked immunosorbent assay. Entering of S phase in response to LPS-stimuli was measured by proliferative assay. Cell cycle analysis by propidium iodide was performed. p21 expression was assessed by real time PCR. Results: Cell proliferation and cell cycle progression in B-1 and B-2 cells, which did not occur in the absence of LPS, required LPS stimulation. After LPS stimulation, B-1 and B-2 cells were shifted to Sand G2/M phases. p21 expression by resting B-1 cells was higher than that of resting B-2 cells. Conclusion: B-1 cells differ from conventional B-2 cells in proliferation, differentiation and cell cycle.