• Korean Journal of School Psychology
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• v.18 no.1
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• pp.31-48
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• 2021

The purpose of this study was to determine whether the retention of university freshmen could be predicted using their peer relationships in a specific department. In this study, retention was defined as a student staying enrolled in their university for a certain period of time. Social relationships are formed through interaction between people, so both students' self-perceptions and others' perceptions of them must be accounted for, so we used a social network analysis that did so. We examined social networks visualizations that allowed for a rich interpretation of numerical information. Participants in this study were freshmen who enrolled in an undergraduate program in 2017, 2018, or 2019. We used the name generator method to determine how quantitative friendship network variables predicted the academic retention up to the first semester of 2020. Cox proportional hazard model analysis showed that the weighted indegree centrality with intimacy positively predicted retention. The results of this study can be used to identify and conduct interventions for students who may be likely to disenroll. However all of the students did not participate in the department, it was difficult to examine their entire peer networks. Thus, this study's results cannot be generalized because the participants are students of a specific major, so further research is needed to produce more generalizable results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1816-1821
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• 2016

Protein secondary structure is important for the study of protein evolution, structure and function of proteins which play crucial roles in most of biological processes. This paper try to effectively extract protein secondary structure information from the large protein structure database in order to predict the protein secondary structure of a query protein sequence. To find more remote homologous sequences of a query sequence in the protein database, we used PSI-BLAST which can perform gapped iterative searches and use profiles consisting of homologous protein sequences of a query protein. The secondary structures of the homologous sequences are weighed combined to the secondary structure prediction according to their relative degree of similarity to the query sequence. When homologous sequences with a neural network predictor were used, the accuracies were higher than those of current state-of-art techniques, achieving a Q3 accuracy of 92.28% and a Q8 accuracy of 88.79%.

• The Journal of the Korea Contents Association
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• v.6 no.7
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• pp.58-68
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• 2006

There are two traditional scheduling methods known as PQ and WRR in the DiffServ network, however, these two scheduling methods have some drawbacks. In this paper, we propose an algorithm that can be adopted in WRR scheduler with making up for weak points of PQ and WRR. The proposed algorithm produces the control discipline by the fuzzy theory to dynamically assign the weight of WRR scheduler with checking the Queue status of each class. To evaluate the performance of the proposed algorithm, We accomplished a computer simulation using NS-2. From simulation results, the proposed algorithm improves the packet loss rate of the EF class traffic to 6.5% by comparison with WRR scheduling method and that of the AF4 class traffic to 45% by comparison with PQ scheduling method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5015-5022
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• 2010

Most of the existing pattern mining techniques are capable of searching patterns according to the continuous change of the spatial information of an object but there is no constraint on the spatial information that must be included in the extracted pattern. Thus, the existing techniques are not applicable to the optimal path search between specific nodes or path prediction considering the nodes that a moving object is required to round during a unit time. In this paper, the precision of the path search according to the spatial hierarchy is analyzed using the Spatial-Temporal Optimal Moving Pattern(with Frequency & Weight) (STOPM(FW)) algorithm which searches for the optimal moving path by considering the most frequent pattern and other weighted factors such as time and cost. The result of analysis shows that the database retrieval time is minimized through the reduction of retrieval range applying with the spatial constraints. Also, the optimal moving pattern is efficiently obtained by considering whether the moving pattern is included in each hierarchical spatial scope of the spatial hierarchy or not.

• Journal of Environmental Science International
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• v.27 no.6
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• pp.371-381
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• 2018

Multifunctional weirs constructed through the Four Major Rivers Restoration Project are operated as management water levels. The purpose of this study was to evaluate the effect of water level in the main stem on the tributary water level according to multifunctional weir operation, because the operation of multifunctional weirs for water level management influences the drainage of tributaries. In this study, water level pressure gauges were installed and spatial and temporal water quality was observed. The LOcally Weighted Scatterplot Smoothing (LOWESS) technique was applied to the Nakdong River and the Baekcheon Junction, both upstream of the Gangjeong-Goryeong weir, in order to analyze water quality trends. When considering the overall analysis and observations, it was found that the water quality forecasting point located at the Baekcheon estuary point should be transferred to the Dosung Bridge, which is located upstream of the Sunwon Bridge.

• Journal of the Korean Magnetic Resonance Society
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• v.21 no.1
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• pp.31-43
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• 2017

Together with radiotherapy, chemotherapy using cytotoxic agents is one of the most common therapies in cancer. Metabolic changes in cancer cells are drawing much attention recently, but the metabolic alterations by anticancer agents have not been much studied. Here, we investigated the effects of commonly used cytotoxic agents on lung normal cell MRC5 and lung cancer cell A549. We employed cis-plastin, doxorubicin, and 5-Fluorouracil and compared their effects on the viability and metabolism of the normal and cancer cell lines. We first established the concentration of the cytotoxic reagents that give differences in the viabilities of normal and cancer cell lines. In those conditions, the viability of A549 decreased significantly, whereas that of MRC5 remained unchanged. To study the metabolic alterations implicated in the viability differences, we obtained the metabolic profiles using $^1H$-NMR spectrometry. The $^1H$-NMR data showed that the metabolic changes of A549 cells are more remarkable than that of MRC5 cells and the effect of 5-FU on the A549 cells is the most distinct compared to other treatments. Heat map analysis showed that metabolic alterations under treatment of cytotoxic agents are totally different between normal and cancer cells. Multivariate analysis and weighted correlation network analysis (WGCNA) revealed a distinctive metabolite signature and hub metabolites. Two different analysis tools revealed that the changes of cell metabolism in response to cytotoxic agents were highly correlated with the Warburg effect and Reductive lipogenesis, two pathways having important effects on the cell survival. Taken together, our study addressed the correlation between the viability and metabolic profiles of MRC5 and A549 cells upon the treatment of cytotoxic anticancer agents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2414-2434
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• 2015

Among numerous localization schemes proposed specifically for Wireless Sensor Network (WSN), the range-free localization algorithms based on the received signal strength indication (RSSI) have attracted considerable research interest for their simplicity and low cost. As a typical range-free algorithm, Approximate Point In Triangulation test (APIT) suffers from significant estimation errors due to its theoretical defects and RSSI inaccuracy. To address these problems, a novel localization method called FIAPIT, which is a combination of an improved APIT (IAPIT) and a fuzzy logic system, is proposed. The proposed IAPIT addresses the theoretical defects of APIT in near (it's defined as a point adjacent to a sensor is closer to three vertexes of a triangle area where the sensor resides simultaneously) and far (the opposite case of the near case) cases partly. To compensate for negative effects of RSSI inaccuracy, a fuzzy system, whose logic inference is based on IAPIT, is applied. Finally, the sensor's coordinates are estimated as the weighted average of centers of gravity (COGs) of triangles' intersection areas. Each COG has a different weight inferred by FIAPIT. Numerical simulations were performed to compare four algorithms with varying system parameters. The results show that IAPIT corrects the defects of APIT when adjacent nodes are enough, and FIAPIT is better than others when RSSI is inaccuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2389-2413
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• 2015

High data rates in long-term evolution (LTE) networks can affect the mobility of networks and their performance. The speed and motion of user equipment (UE) can compromise seamless connectivity. However, a proper handover (HO) decision can maintain quality of service (QoS) and increase system throughput. While this may lead to an increase in complexity and operational costs, self-optimization can enhance network performance by improving resource utilization and user experience and by reducing operational and capital expenditure. In this study, we propose the self-optimization of HO parameters based on fuzzy logic control (FLC) and multiple preparation (MP), which we name FuzAMP. Fuzzy logic control can be used to control self-optimized HO parameters, such as the HO margin and time-to-trigger (TTT) based on multiple criteria, viz HO ping pong (HOPP), HO failure (HOF) and UE speeds. A MP approach is adopted to overcome the hard HO (HHO) drawbacks, such as the large delay and unreliable procedures caused by the break-before-make process. The results of this study show that the proposed method significantly reduces HOF, HOPP, and packet loss ratio (PLR) at various UE speeds compared to the HHO and the enhanced weighted performance HO parameter optimization (EWPHPO) algorithms.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.128-131
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• 2006

There are two traditional scheduling methods known as PQ and WRR in the DiffServ network, however, these two scheduling methods have some drawbacks. In this paper, we propose an algorithm that can be adopted in WRR scheduler with making up for weak points of PQ and WRR. The proposed algorithm produces the control discipline by the fuzzy theory to dynamically assigns the weight of WRR scheduler with checking the Queue status of each class. To evaluate the performance of the proposed algorithm, We accomplished a computer simulation using NS-2. In result, the proposed algorithm enhances the packet discard rate at the EF class than WRR scheduling method and the AF4 class than PQ scheduling method.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.419-424
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• 2012

This paper discusses the state-of-the-art techniques in real-time state estimation for the Smart Microgrids. The most popular method used in traditional power system state estimation is a Weighted Least Square(WLS) algorithm which is based on Maximum Likelihood(ML) estimation under the assumption of static system state being a set of deterministic variables. In this paper, we present a survey of dynamic state estimation techniques for Smart Microgrids based on Belief Propagation (BP) when the system state is a set of stochastic variables. The measurements are often too sparse to fulfill the system observability in the distribution network of microgrids. The BP algorithm calculates posterior distributions of the state variables for real-time sparse measurements. Smart Microgrids are modeled as a factor graph suitable for characterizing the linear correlations among the state variables. The state estimator performs the BP algorithm on the factor graph based the stochastic model. The factor graph model can integrate new models for solar and wind correlation. It provides the Smart Microgrids with a way of integrating the distributed renewable energy generation. Our study on Smart Microgrid state estimation can be extended to the estimation of unbalanced three phase distribution systems as well as the optimal placement of smart meters.