• Korean Journal of Radiology
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• v.23 no.8
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• pp.811-820
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• 2022

Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825-0.910) in the training cohort and 0.890 (0.844-0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcomes.

• Journal of Korean society of Dental Hygiene
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• v.12 no.3
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• pp.521-531
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• 2012

Objectives : The aim of this study was to evaluate the relation between the state of dental health(number of natural teeth) and nutritional status of Korean elderly using Korean Dietary Reference Intakes, which was an objective standard for nutritional intake based on database of Korea National Health and Nutrition Examination Survey, large scale of sample obtained by the government. Methods : Complex sampling procedure was used to analyze the fourth data(2007-2009) of Korea National Health and Nutrition Examination Survey. When preparing planning file, the estimator of variance as a stratification variance (variance name : kstrata), population of survey unit as a cluster variance(variance name : PSU), and previous exam and nutritional related weighted as a weighted were analyzed by considering reproduced survey and nutritional related total weighted. Complex samples chi-square test was used to estimate the relation between number of natural teeth and inadequate intake and relation factors included in the model were analyzed by complex samples logistic regression analysis. Results : The group of edentulous had a higher risk to intake less nutrient, except calcium, riboflavin and vitamin C than recommended level comparing to reference group which had natural teeth more than 20(phosphate : OR=1.763; 95% CI=1.273-2.443, thiamine : OR=1.748; 95% CI=1.276-2.395, protein : OR=1.610; 95% CI=1.213-2.138). Conclusions : The number of teeth in Korean elderly over 65 years old had a relation with nutritional status in this investigation. Especially, intake level of nutrients was different between the edentulous group and the reference group. Therefore, dental health care is needed from young and middle age to keep health dental condition for through whole life as well as old age. Although the dental condition of the aged is not good, it is evitable to educate them about the relation between dental health and nutritional ingestion to take balanced nutrition, we think.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.5
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• pp.401-415
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• 2005

Owing to the improved wireless communication technologies, it is possible to provide streaming service of multimedia with PDAs and mobile phones in addition to desktop PCs. Since mobile client devices have low computing power and low network bandwidth due to wireless network, the transcoding technology to adapt media for mobile client devices considering their characteristics is necessary. Transcoding servers transcode the source media to the target media within corresponding grades and provide QoS in real-time. In particular, an effective load balancing policy for transcoding servers is inevitable to support QoS for large scale mobile users. In this paper, the resource weighted load distribution policy is proposed for a fair load balance and a more scalable performance in cluster-based transcoding servers. Our proposed policy is based on the resource weighted table and number of maximum supported users, which are pre-computed for each pre-defined grade. We implement the proposed policy on cluster-based transcoding servers and evaluate its fair load distribution and scalable performance with the number of transcoding servers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3378-3393
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• 2014

We have witnessed the rapid development of information technology in recent years. One of the key phenomena is the fast, near-exponential increase of data. Consequently, most of the traditional data classification methods fail to meet the dynamic and real-time demands of today's data processing and analyzing needs--especially for continuous data streams. This paper proposes an improved incremental learning algorithm for a large-scale data stream, which is based on SVM (Support Vector Machine) and is named DS-IILS. The DS-IILS takes the load condition of the entire system and the node performance into consideration to improve efficiency. The threshold of the distance to the optimal separating hyperplane is given in the DS-IILS algorithm. The samples of the history sample set and the incremental sample set that are within the scope of the threshold are all reserved. These reserved samples are treated as the training sample set. To design a more accurate classifier, the effects of the data volumes of the history sample set and the incremental sample set are handled by weighted processing. Finally, the algorithm is implemented in a cloud computing system and is applied to study user behaviors. The results of the experiment are provided and compared with other incremental learning algorithms. The results show that the DS-IILS can improve training efficiency and guarantee relatively high classification accuracy at the same time, which is consistent with the theoretical analysis.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1285-1291
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• 2016

To quantify an concept we often use Likert summated rating scale of original or standardized variables in case the variables are relatively less. When variables have different scales, standardized values tends to be used rather than the original values. This is also true in evaluating systems. For example, we may use standardized values of local tax levy, population, and etc. and use the summed value of the standardized values to access the degrees of development. In this paper, we propose using a data-driven weighted sum for a scoring system and the way how to obtain the weights. We apply the proposed method to a real data set and find that proposed method is better than the usual summated rating scale.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.57-65
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• 2010

In this paper, we propose a new real-time algorithm detecting the flame and smoke in digital CCTV images. Because the forest fire causes the enormous human life and damage of property, the early management according to the early sensing is very important. The proposed algorithm for monitoring forest fire is classified into the flame sensing and detection of smoke. The flame sensing algorithm detects a flame through the conditional test at YCbCr color model from the single frame. For the detection of smoke, firstly the background range is set by using differences between current picture and the average picture among the adjacent frames in the weighted value, and the pixels which get out of this range and have a gray-scale are detected in the smoke area. Because the proposed flame sensing algorithm is stronger than the existing algorithms in the change of the illuminance according to the quantity of sunshine, and the smoke detection algorithm senses the pixel of a gray-scale with the smoke considering the amount of change for unit time, the effective early forest fire detection is possible. The experimental results indicate that the proposed algorithm provides better performance than existing algorithms.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.67-74
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• 2023

A semiconductor fabrication facility(FAB) is one of the most capital-intensive and large-scale manufacturing systems which operate under complex and uncertain constraints through hundreds of fabrication steps. To improve fab performance with intuitive scheduling, practitioners have used weighted-sum scheduling. Since the determination of weights in the scheduling significantly affects fab performance, they often rely on simulation-based decision making for obtaining optimal weights. However, a large-scale and high-fidelity simulation generally is time-intensive to evaluate with an exhaustive search. In this study, we investigated three sampling methods (i.e., Optimal latin hypercube sampling(OLHS), Genetic algorithm(GA), and Decision tree based sequential search(DSS)) for the optimization. Our simulation experiments demonstrate that: (1) three methods outperform greedy heuristics in performance metrics; (2) GA and DSS can be promising tools to accelerate the decision-making process.

• Journal of Audiology & Otology
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• v.23 no.1
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• pp.53-58
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• 2019

Background and Objectives: The aim of the present study was to assess the feasibility of a PC-based facial asymmetry assessment program (PC-FAAP) and to compare the results of PC-FAAP with subjective regional scoring by raters in acute unilateral peripheral facial nerve paralysis (FNP). Subjects and Methods: Participants were divided into 3 groups with 8 participants per group: group I, normal; group II, mild to moderate FNP; and group III, severe FNP. Using the PC-FAAP, the mouth asymmetry ratio (MAR), eyebrow asymmetry ratio (EAR), and complete eye closure asymmetry ratio (CAR) were calculated by comparing the movement of tracking points on both sides. The FNP grading scale (FGS) integrated each score, and the scores were weighted with a ratio of 5:3:2 (MAR:CAR:EAR). Subjective regional scoring was measured on a 0-100 scale score by three otologists. PC-FAAP and subjective scoring were compared in each group regarding the consistency of the results. Results: The mean scores of the MAR, EAR, CAR, and FGS of each group were significantly different. PC-FAAP showed significant differences between the three groups in terms of MAR, EAC, CAR, and FGS. PC-FAAP showed more consistent results than subjective assessment (p<0.001). The PC-FAAP was significantly more consistent in group I and group III (p<0.001 and p=0.002, respectively). FGS in group III was the only parameter that showed a more consistent result in PC-FAAP than the subjective scoring (p=0.008). Conclusions: An FNP grading system using a PC-based program may provide more consistent results, especially for severe forms.

• Korean Journal of Audiology
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• v.23 no.1
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• pp.53-58
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• 2019

Background and Objectives: The aim of the present study was to assess the feasibility of a PC-based facial asymmetry assessment program (PC-FAAP) and to compare the results of PC-FAAP with subjective regional scoring by raters in acute unilateral peripheral facial nerve paralysis (FNP). Subjects and Methods: Participants were divided into 3 groups with 8 participants per group: group I, normal; group II, mild to moderate FNP; and group III, severe FNP. Using the PC-FAAP, the mouth asymmetry ratio (MAR), eyebrow asymmetry ratio (EAR), and complete eye closure asymmetry ratio (CAR) were calculated by comparing the movement of tracking points on both sides. The FNP grading scale (FGS) integrated each score, and the scores were weighted with a ratio of 5:3:2 (MAR:CAR:EAR). Subjective regional scoring was measured on a 0-100 scale score by three otologists. PC-FAAP and subjective scoring were compared in each group regarding the consistency of the results. Results: The mean scores of the MAR, EAR, CAR, and FGS of each group were significantly different. PC-FAAP showed significant differences between the three groups in terms of MAR, EAC, CAR, and FGS. PC-FAAP showed more consistent results than subjective assessment (p<0.001). The PC-FAAP was significantly more consistent in group I and group III (p<0.001 and p=0.002, respectively). FGS in group III was the only parameter that showed a more consistent result in PC-FAAP than the subjective scoring (p=0.008). Conclusions: An FNP grading system using a PC-based program may provide more consistent results, especially for severe forms.

• Safety and Health at Work
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• v.14 no.4
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• pp.476-482
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• 2023

Introduction: There is a growing global interest in the issue of precarious employment. We aimed to analyze the characteristics and socio-demographic distribution of precarious employment using a summative score approach. Methods: To operationalize precarious employment, we utilized data from the Korean Working Conditions Survey and focused on three distinct dimensions: employment insecurity, income inadequacy, and a lack of rights and protections. By constructing a summative scale ranging from -16 to 2, with lower scores indicating higher precariousness, we measured employment precariousness among Korean wage workers. To compare employment precariousness according to survey participant characteristics, we employed the Wilcoxon Rank Sum Test. Results: We analyzed a weighted number of 38,432 workers. The overall sample showed a median (Q1, Q3) summative scale score of -3 (-6, -1). The median summative score was lower for women compared to men (men: -2; women: -5; p < 0.001), as well as for young or older workers compared to middle-aged workers (young: -4; middle-aged: -2; older: -5; p < 0.001). Similarly, workers with lower educational levels (middle school or below: -8; high school: -5; college or above: -2; p < 0.001) and non-white collar workers (blue collar: -5; service/sales worker: -6; white collar: -2; p < 0.001) experienced higher levels of employment precariousness. Conclusion: Our findings indicate that certain vulnerable groups, such as women, young or older adults, workers with low educational attainment, and caregiving or low-skilled elementary workers, are disproportionately exposed to high employment precariousness. Active policy interventions are needed to improve the employment quality of vulnerable groups.