• Nutrition Research and Practice
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• 제12권1호
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• pp.69-77
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• 2018

BACKGROUND/OBJECTIVES: Metabolic risk factors should be managed effectively in patients with type 2 diabetes mellitus (T2DM) to prevent or delay diabetic complications. This study aimed to compare the self-management levels of diet and metabolic risk factors in patients with T2DM, according to the duration of illness, and to examine the trends in self-management levels during the recent decades. SUBJECTS/METHODS: Data were collected from the Korea National Health and Nutrition Examination Surveys (KNHANES, 1998-2014). In our analysis, 4,148 patients with T2DM, aged ${\geq}30years$, were categorized according to the duration of their illness (< 5 years, 5-9 years, and ${\geq}10years$). Demographic and lifestyle information was assessed through self-administered questionnaires, and biomarker levels (e.g., fasting glucose level, blood pressure, or lipid level) were obtained from a health examination. Dietary intake was assessed by a 24-recall, and adherence level to dietary guidelines (meal patterns and intake levels of calories, carbohydrates, vegetable/seaweed, sodium, and alcohol) were assessed. Multivariable generalized linear regression and unconditional logistic regression models were used to compare the prevalence rates of hyperglycemia, dyslipidemia, and hypertension according to the duration of patients' illness, accounting for the complex survey design of the KNHANES. RESULTS: In the multivariable adjusted models, patients with a longer duration (${\geq}10years$) of T2DM had a higher prevalence of hyperglycemia than those with a shorter duration of T2DM (< 5 years) (odds ratio 2.20, 95% confidence interval 1.61-3.01, P for trend < 0.001). We did not observe any associations of disease duration with the prevalence of hypertension and dyslipidemia. In addition, the adherence levels to dietary recommendations did not significantly differ according to disease duration, except adherence to moderate alcohol consumption. There were significant decreasing trends in the prevalence of hyperglycemia in patients with a duration of illness ${\geq}10years$ (P for trend = 0.004). CONCLUSION: Although the proportion of patients with adequate control of glucose levels has improved in recent decades, poorer self-management has been found in those with a longer disease duration. These findings suggest the need for well-planned and individualized patient education programs to improve self-management levels and quality of life by preventing or delaying diabetic complications.

• Clinical and Experimental Pediatrics
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• 제62권2호
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• pp.55-61
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• 2019

Purpose: Myotonic dystrophy, also known as dystrophia myotonica (DM), is an autosomal dominant disorder with 2 genetically distinct forms. DM type 1 (DM1) is the more common form and is caused by abnormal expansion of cytosine/thymine/guanine (CTG) repeats in the DM protein kinase (DMPK ) gene. Our study aimed to determine whether the age of onset is correlated with CTG repeat length in a population of pediatric patients with DM1. Methods: We retrospectively identified 30 pediatric patients with DM1 that underwent DMPK testing, of which the clinical data of 17 was sufficient. The cohort was divided into 2 subgroups based on the clinical phenotype (congenital-onset vs. late-onset) and number of CTG repeats (<1,000 vs. ${\geq}1,000$). Results: We found no significant difference between the age of onset and CTG repeat length in our pediatric patient population. Based on clinical subgrouping, we found that the congenital-onset subgroup was statistically different with respect to several variables, including prematurity, rate of admission to neonatal intensive care unit, need for respiratory support at birth, hypotonia, dysphagia, ventilator dependence, and functional status on last visit, compared to the late-onset subgroup. Based on genetic subgrouping, we found a single variable (poor feeding in neonate) that was significantly different in the large CTG subgroup than that in the small CTG subgroup. Conclusion: Clinical variables exhibiting statistically significant differences between the subgroups should be focused on prognosis and designing tailored management approaches for the patients; our findings will contribute to achieve this important goal for treating patients with DM1.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2007년도 학술대회
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• pp.371-375
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• 2007

In this paper, we have implemented the device management system to upgrade T-PAK software in mobile phone. The hybrid scheduling method and selective upgrade method are proposed. Hybrid scheduling method is based on distribution of delivery data in accordance with network traffic load and service priority from device management server to mobile phone. Selective upgrade method manages DSL classified by T-PAK software version to be upgrade using version management established in OMA DM SCOMO. Key mechanism of selective upgrade method is to only deliver DSL to be replaced to the mobile phone. We made an experiment on two methods using MS-700T terminals. The experimental result shows that the proposed method is faster than normal from delivery time standpoint.

• 한국콘텐츠학회논문지
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• 제14권10호
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• pp.198-209
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• 2014

당뇨병은 유병률과 합병증으로 인한 사망률이 지속적으로 증가하는 질병이다. 본 연구는 성인의 당뇨병 유병률 영향요인을 확인함으로써 당뇨병 유병률의 감소를 위한 중재전략 개발의 기초자료를 제공하고자 시도되었다. 연구대상자는 19세 이상 성인으로 2012년 국민건강영양조사 원시자료를 활용하여 분석하였으며, 5995명의 자료가 분석에 사용되었다. 수집된 자료는 SPSS 18.0 프로그램의 복합표본 분석 모듈을 사용하여 가중치를 부여한 후 분석하였다. 연구결과 19세 이상 성인의 당뇨병 유병률은 10.5%였고, 당뇨병 유병 오즈비는 학력에서 대졸 이상에 비해 중졸은 2.51배, 주관적 건강상태가 매우 좋은 경우에 비해 매우 나쁜 경우 4.77배, 비만인 경우 1.44배, 고혈압을 진단받은 경우 2.57배, 고지혈증을 진단받은 경우 2.63배, 체중조절을 하지 않는 경우 1.31배, 식이요법을 하는 경우 2.75배로 높았다. 본 연구는 당뇨병 유병률을 예측하는 변수로 교육수준, 주관적 건강상태, 비만 유병 여부, 고혈압 의사진단 여부, 고지혈증 의사진단 여부, 체중조절 여부, 식이요법 여부를 밝힘으로써 당뇨병 유병률을 감소시키기 위한 간호중재와 연구방향을 제시하였다.

• 아시안잔디학회지
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• 제1권1호
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• pp.18-29
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• 1987

This study was carried out to examine the effect of nitrogen application and clipping interval on the characteristics of several turf components of korean lawngrass for the basic data of lawn management. It was treated by Split plot design with three replications. The main plots were nitrogen levels with 0, 350, and 700kgN / ha, and the sub plots were clipping intervals with 10, 20, and 30 days The results obtained are summarized as follows ; 1. Increasing the rate of nitrogen fertilizer and frequent clipping increased tiller number of korean lawngrass and the maximum number of tillers obtained in October were recorded from 700kgN application and clipping treatment of 10 days interval. Meanwhile, treatment of 350kgN with 10 days clipping interval increased tillers much more than those of 700kgN with 20 and 30 days clipping intervals. 2. The average number of green leaves occurred during the growth period maximized by applying 700 kgN and clipping 10 days interval. 3. Increasing tiller numbers significantly decreased tops DM weight per tiller by clippng plants at interval of 10 and 20 days, irrespective of nitrogen applied, and with nil N, at the interval of 30 days. By applying 700kgN however, tops DM weight per tiller increased as the number of tillers increased consistently. 4. The highest tops DM weight was achieved from late August to early September by applying 350 and 700kgN. 5. During the growth period, nitrogen application increased unders(stolon+root) DM weight, and, at the same level of nitrogen applied, the increase in stolon DM weight enhanced by lengthening the clipping interval to 30 days. 6. Nitrogen efficiency to green leaves, stolon nodes and DM weight of root with high nitrogen was achieved as clipping interval was shortened.

• Journal of Nutrition and Health
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• 제49권5호
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• pp.304-312
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• 2016

본 연구는 2007~2012년 국민건강영양조사 자료를 이용하여 30세 이상 제2형 당뇨병 여성 환자의 과일류 및 생선류 등의 식품섭취량과 심혈관질환 위험인자와의 관련성을 분석하였다. T2DM군이 NFG군에 비해 과일류 및 생선류의 섭취량이 유의적으로 낮았고 이들의 섭취량이 증가할수록 고중성지방혈증의 위험성이 유의적으로 감소하는 것으로 나타났다. 또한, 과일류와 생선류 섭취량은 각각 중앙값 이상으로 많이 섭취한 군 (FF3)이 각각 중앙값 이하로 섭취한 군 (FF1)에의 비해 TG 농도가 높을 위험이 유의적으로 낮았다. 이러한 결과는 과일류에 김치를 제외한 채소류, 버섯류, 해조류의 섭취량을 포함시켜 분석했을 때에도 같은 결과를 나타내었다. 따라서, 한국인 제2형 당뇨병여성 환자의 과일류 및 생선류의 섭취가 심혈관질환에 긍적적인 영향을 미치는 것으로 보이며, 과일류나 생선류 중 어느 한 종류만 많이 섭취하기보다는 두 종류를 모두 적절히 섭취하는 것이 심혈관 질환 위험성을 낮추는데 효과적일 것으로 사료된다.

• 지식경영연구
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• 제19권2호
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• pp.151-162
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• 2018

Response surface methodology (RSM) is one of popular tools to support a systematic improvement of quality of design in the product and process development stages. It consists of statistical modeling and optimization tools. RSM can be viewed as a knowledge management tool in that it systemizes knowledge about a manufacturing process through a big data analysis on products and processes. The conventional RSM aims to optimize the mean of a response, whereas dual-response surface optimization (DRSO), a special case of RSM, considers not only the mean of a response but also its variability or standard deviation for optimization. Recently, a posterior preference articulation approach receives attention in the DRSO literature. The posterior approach first seeks all (or most) of the nondominated solutions with no articulation of a decision maker (DM)'s preference. The DM then selects the best one from the set of nondominated solutions a posteriori. This method has a strength that the DM can understand the trade-off between the mean and standard deviation well by looking around the nondominated solutions. A posterior method has been proposed for DRSO. It employs an interval selection strategy for the selection step. This strategy has a limitation increasing inefficiency and complexity due to too many iterations when handling a great number (e.g., thousands ~ tens of thousands) of nondominated solutions. In this paper, a TOPSIS-based method is proposed to support a simple and efficient selection of the most preferred solution. The proposed method is illustrated through a typical DRSO problem and compared with the existing posterior method.

• Asia pacific journal of information systems
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• 제32권3호
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• pp.496-513
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• 2022

Artificial intelligence or big data technologies can benefit finance companies such as those in the insurance sector. With artificial intelligence, companies can develop better customer segmentation methods and eventually improve the quality of customer relationship management. However, the application of AI-based customer segmentation in the insurance industry seems to have been unsuccessful. Findings from our interviews with sales agents and customer service managers indicate that current customer segmentation in the Korean insurance company relies upon individual agents' heuristic decisions rather than a generalizable data-based method. We propose guidelines for AI-based customer segmentation for the insurance industry, based on the CRISP-DM standard data mining project framework. Our proposed guideline provides new insights for studies on AI-based technology implementation and has practical implications for companies that deploy algorithm-based customer relationship management systems.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.99-104
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• 2003

In this research, we proposed the mechanism to develop self evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most former researchers tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, thy have some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, many of researchers had tried to develop an automatic knowledge extraction and refining mechanisms. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, in this study, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference. Our proposed mechanism has five advantages empirically. First, it could extract and reduce the specific domain knowledge from incomplete database by using data mining algorithm. Second, our proposed mechanism could manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it could construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems). Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic. Fifth, RDB-driven forward and backward inference is faster than the traditional text-oriented inference.

• 한국산학기술학회논문지
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• 제14권4호
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• pp.1774-1780
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• 2013

본 연구는 당뇨 환자를 대상으로 신경병증 통증과 혈당조절정도 및 자가관리간의 관계를 파악하는 서술적 상관관계 연구이다. 자료는 일 대학교 병원의 내분비 내과에서 2011년 5월 10일부터 5월 31일까지 당뇨로 방문한 환자 중 연구기준에 적합한 108명을 대상으로 자가보고식 설문지와 의무기록을 이용하여 수집되었다. 자료분석은 SPSS WIN 18.0을 이용하여 서술통계와 Pearson's correlation coefficient를 실시하였다. 연구 결과 당뇨환자의 통증은 $9.3{\pm}0.4$점이었으며 당화혈색소 수치는 7.5% 이상인 군이 33.3%를 차지하였고 자가관리는 $5.40{\pm}0.76$점이었다. 당뇨환자의 신경병증 통증은 혈당조절 정도가 양호할수록(r=.18, p=.035), 자가관리 수행정도가 높을수록(r=-.19, p=.023) 적었다. 결론적으로 당뇨환자의 신경병증 통증을 조절하기 위하여 보다 엄격한 혈당관리와 자가관리를 향상시키는 노력이 필요하다.