• International journal of advanced smart convergence
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• 제11권4호
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• pp.28-40
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• 2022

Although precise temperature control in the heat treatment process is a key factor in process reliability, there are many cases where there is no separate heat source control optimization system in the field. To solve this problem, the program monitors the temperature data according to the heat source change through sensor communication in a recursive method based on multiple variables that affect the process, and the target heat source value and the actual heat treatment heat source to match the internal air temperature and material temperature. A control optimization system was constructed. Through this study, the error rate between the target temperature and the atmosphere (material surface) temperature of around 10.7% with the existing heat source control method was improved to an improved result of around 0.1% using a process optimization algorithm and system.

• 대한간호학회지
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• 제34권3호
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• pp.430-439
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• 2004

Purpose: The purpose of this study was to examine risk factors for sexual behaviors in Korean female high school students. Methods: Data was collected by a written questionnaire from June 22 to July 18, 2002 from 522 girls, who were stratified samples from a target population of 63,375 11th grade students from 200 regular high schools and 70 vocational high schools in Seoul, Korea. We conducted multiple regression analysis using the SAS pc＋ program. Results: Risk factors for intimate behaviors were association with boy friends, differential association, family attachment, and family abuse experience. These variables cause 68% of intimate behaviors. Risk factors for sexual experiences were differential association, association with boy friend, and family attachment. These variables cause 14% of sexual experiences. Conclusion: Efforts to reduce sexual behaviors in girls should include the possible role of peers and develop peer leader programs.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2003년도 가을 학술발표논문집 Vol.30 No.2 (1)
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• pp.196-198
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• 2003

Virtually every digital signal processors(DSPs) support on-chip multi- memory banks that allow the processor to access multiple words of data from memory in a single instruction cycle. Also, all existing fixed-point DSPs have irregular architecture of heterogeneous register which contains multiple register files that are distributed and dedicated to different sets of instructions. Although there have been several studies conducted to efficiently assign data to multi-memory banks, most of them assumed processors with relatively simple, homogeneous general-purpose resisters. Therefore, several vendor-provided compilers fer DSPs were unable to efficiently assign data to multiple data memory banks. thereby often failing to generate highly optimized code fer their machines. This paper presents an algorithm that helps the compiler to efficiently assign data to multi- memory banks. Our algorithm differs from previous work in that it assigns variables to memory banks in separate, decoupled code generation phases, instead of a single, tightly-coupled phase. The experimental results have revealed that our decoupled algorithm greatly simplifies our code generation process; thus our compiler runs extremely fast, yet generates target code that is comparable In quality to the code generated by a coupled approach

• 한국식품과학회지
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• 제23권1호
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• pp.88-92
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• 1991

스크류조합을 달리한 실험실용 twin-screw extruder를 사용하여 corn grit를 원료 투입량($30{\sim}60\;kg/hr$), 스크류 회전속도($200{\sim}400\;rpm$) 및 die hole 수($2{\sim}6$개) 범위에서 압출하면서 측정된 system parameters(압출온도, 기계적 에너지 소모율, 평균 체류시간)가 압출물의 특성을 나타내는 target parameters(수분 증발량, 수분 용해도지수 및 수분 흡착지수)에 미치는 영향을 스크류 조합별과 전체 실험결과를 다중회귀분석을 통하여 회귀식으로 나타내면, 스크류조합별 관계식에서는 상관계수가 0.90 이상 이었으며, 구획하지 않은 전체 회귀식에서는 0.80 정도의 상관계수를 보였다. 이상의 결과는 system analysis approach을 이용하면, 상이한 extruder사이의 조업자료 중 system parameters의 분석을 통하여 목적 제품의 특성을 예측할 수 있는 가능성을 보여준다고 생각된다.

• 소성∙가공
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• 제26권5호
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• pp.271-276
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• 2017

A tee is the most common pipefitting used to combine or divide fluid flow. Tees can connect pipes of different diameters or change the direction of a pipe run. To manufacture tee type of stainless steel pipe, combinations of punch piercing and burr forming have been widely used in the industry. However, such method is considerably time consuming with regard to performing empirical work necessary to attain process conditions to prevent upper end tearing of the tee product and meet target tee height. Numerous experiments have shown that the piercing profile is the main cause of defects mentioned above. Furthermore, the mold design is formed through trial and error according to pipe diameters and changes in requirements. Thus, the objective of this study was to perform piercing and burring process analysis via finite element analysis using DYNAFORM to resolve problems mentioned above. An optimization design method was used to determine the piercing punch profile. Three radii of the piercing punch (i.e., large, small, and joined radii) were selected as design variables to minimize thinning of a tee pipe. Based on results of correlation and multiple regression analyses, we developed a predictive approximation model to satisfy requirements for both thickness reduction and target height. The new piercing punch profile was then applied to actual tee forming using the developed prediction equation. Model results were found to be in good agreement with experimental results.

• Nutrition Research and Practice
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• 제8권4호
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• pp.425-431
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• 2014

BACKGROUND/OBJECTIVES: The study objectives were to examine the participation rate in food assistance programs and explore the factors that contribute to such participation among the Korean elderly population. SUBJECTS/METHODS: The study sample comprised 3,932 respondents aged 65 years or older who were selected from a secondary data set, the fourth Korean Welfare Panel Study (KoWePS). The factors, related to participation in programs were examined based on the predisposing, enabling and need factors of the help-seeking behavior model. Multiple logistic regression analysis was used to select the best contributors among the factors related to program participation. RESULTS: The predisposing rate in food assistance programs was 8.5% (7.1% for men and 10.4% for women). When all variables were included in the model, living without spouse, no formal education, low income, having social security benefits and food insecurity in elderly men, and age, low income, having social security benefits and feeling poor in elderly women were significantly related to a higher tendency to program participation. CONCLUSIONS: The predisposing and need factors, such as living without spouse, low education level, food insecurity and feeling poor were important for program participation, as well as enabling factors, such as household income and social security benefits. A comprehensive approach considering these factors to identify the target population for food assistance programs is needed to increase the effectiveness and target population penetration of these programs.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2002년도 Proceedings
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• pp.146-149
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• 2002

The aim of stereotactic radiosurgery(SRS) is to deliver a high dose to a target region and a low dose to critical organ through only one or a few irradiation. To satisfy this aim, optimized irradiating conditions must be searched in the planning. Thus, many mathematical methods such as gradient method, simulated annealing and genetic algorithm had been proposed to find out the conditions automatically. There were some limitations using these methods: the long calculation time, and the difficulty of unique solution due to the different shape of tumor. In this study, optimization protocol using ideal models and data base was proposed. Proposed optimization protocol constitutes two steps. First step was a preliminary work. Some possible ideal geometry shapes, such as sphere, cylinder, cone shape or the combination, were assumed to approximate the real tumor shapes. Optimum variables such as isocenter position or collimator size, were determined so that the high dose region could be shaped to fit ideal models with the arrangement of multiple isocenter. Data base were formed with those results. Second, any shaped real targets were approximated to these models using geometry comparison. Then, optimum variables for ideal geometry were chosen from the data base predetermined, and final parameters were obtained by adjusting these data. Although the results of applying the data base to patients were not superior to the result of optimization in each case, it can be acceptable as a starting point of plan.

• 종양간호연구
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• 제2권1호
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• pp.17-26
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• 2002

Purpose: This study was conducted to evaluate the effects of aerobic dance on physical functionnings of women with mastectomy. The study was single group pre- & post-test time series design. The aerobic dance program was performed three times a week for eight weeks, 45${\sim}$60 minutes per session. Method: The research variables used in the study were the period(seconds) of exercise that was taken for target heart rate, activity systolic pressure, range of motion of shoulder joint in affected side, and flexibility for physical functionnings. The data were analyzed with repeated measure ANOVA and Bonferroni multiple comparisons. Results: Over the period of aerobic dance, the degree of all the research variables were changed significantly, and also differed significantly every 2 to 4 weeks. The period(seconds) of exercise that was taken for target heart rate (p <.000), systolic pressure in exercise(p =.019), range of motions of shoulder joint on the affected side(flexion, abduction, over-adduction, over-extension, external & internal rotation), and flexibility(sit & reach, back & reach) (p= .003; p=.001; p(.001; p<.001; p= .014; p<.001; p=.036; p<.001) were differed significantly respectively. Conclusion: The results suggest that the aerobic dance program for women with mastectomy can improve and recover cardiopulmonary endurance and ROM of shoulder joint and that the period of exercise had to be performed over six to eight weeks and three times a week at least.

• 가정과삶의질연구
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• 제32권6호
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• pp.19-30
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• 2014

The purpose of this study was to identify the relationships between Healthy Family Support Center (HFSC) program participation and family strengths and program needs based on HFSC participants' individual, family, and community characteristics. A total of 695 HFSC participants who were married and had participated in HFSC programs were recruited through 25 local HFSCs in Seoul. A multiple regression method was conducted for data analysis. The major findings are as follows. Family strengths was related to the variables of age, education, monthly household income, and participation in family counseling and sharing family care programs. In terms of program needs, the variables of marital conflict, difficulty in care, financial distress, family strengths, and family-friendly community were associated with HFSC program needs while participants' socio-demographic characteristics were not related to program needs. This study highlights that HFSC programs have different target populations considering that the level of family strengths was different among the various programs' participants. In addition, program needs are different depending upon the HFSC participants' experiences in the family and community. These findings suggest that it is important to consider participants' family and community characteristics as well as participants' socio-demographic characteristics to provide appropriate programs for all HFSC participants.

• Asia pacific journal of information systems
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• 제7권1호
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• pp.67-83
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• 1997

The utility of learning techniques in investment analysis has been demonstrated in many areas, ranging from forecasting individual stocks to entire market indexes. To date, however, the application of artificial intelligence to financial forecasting has focused largely on short predictive horizons. Usually the forecast window is a single period ahead; if the input data involve daily observations, the forecast is for one day ahead; if monthly observations, then a month ahead; and so on. Thus far little work has been conducted on the efficacy of long-term prediction involving multiperiod forecasting. This paper examines the impact of alternative procedures for extended prediction using knowledge discovery techniques. One dimension in the study involves temporal granularity: a single jump from the present period to the end of the forecast window versus a web of short-term forecasts involving a sequence of single-period predictions. Another parameter relates to the numerosity of input variables: a technical approach involving only lagged observations of the target variable versus a fundamental approach involving multiple variables. The dual possibilities along each of the granularity and numerosity dimensions entail a total of 4 models. These models are first evaluated using neural networks, then compared against a multi-input jump model using case based reasoning. The computational models are examined in the context of forecasting the S&P 500 index.