• 한국치위생학회지
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• 제15권4호
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• pp.623-629
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• 2015

Objectives: The purpose of the study is to investigate the relationships between multiple intelligence, academic self-efficacy, satisfaction with major in dental hygiene students. Methods: A self-reported questionnaire was filled out by 490 dental hygiene students in Jeonbuk from March to April, 2015. The questionnaire consisted of 119 questions of multiple intelligences, 28 questions of academic self-efficacy, 5 questions of satisfaction with major by Likert 5 scale. Data were analyzed by descriptive statistics, Pearson's correlation test, and stepwise multiple regression test using SPSS 18.0 program. Results: The students had the highest score in interpersonal intelligence(3.57) and the lowest in naturalist intelligence(2.66). There was a positive correlation between the multiple intelligences, academic self-efficacy and satisfaction with major(p<0.05). The impact of multiple intelligences on academic self-efficacy was influenced by logical-mathematical intelligence, intrapersonal intelligence, musical intelligence, bodily-kinesthetic intelligence, and linguistic intelligence(p<0.05). The variables that had an impact on multiple intelligences and satisfaction with major were interpersonal intelligence and intrapersonal intelligence(p<0.01). Conclusions: The development of multiple intelligences can enhance the satisfaction with the major, quality of education, academic self-efficacy in the dental hygiene students.

• Child Health Nursing Research
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• 제13권4호
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• pp.427-435
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• 2007

Purpose: This study presents the findings of various research on human intelligence and Multiple Intelligence Theory and suggested the implications of Multiple Intelligence Theory-based approach to the nursing education for the ill children. Method: Research objectives were accomplished by conducting a literature review. The main areas of the literature review included the Multiple Intelligence Theory, and it's application case for the children with learning disorder. Results: Dissatisfaction with traditional IQ tests has led to the development of a number of alternative theories, all of which suggest that intelligence is the result of a number of independent abilities that uniquely contribute to human performance. Among them, Multiple Intelligences Theory led to break intelligence down into at least eight different components: logical, linguistic, spatial, musical, kinesthetic, naturalist, intra-personal and interpersonal intelligences. In addition, Multiple Intelligence Theory and it's application case believes that every topic can be effectively taught and achieved using six entry points framework. Conclusions: The educational implications of Multiple Intelligence Theory in view of the health education and education in the children's hospital school should be considered for the ill children2's better education in a hospital setting.

• Journal of information and communication convergence engineering
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• 제20권1호
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• The Journal of Asian Finance, Economics and Business
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• 제7권1호
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• pp.29-36
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• 2020

Stock price multiple is one of the most well-known equity valuation technique used to forecast equity price. It measures by multiplying "the ratio of stock price to a value driver" by a value driver. The value driver can be earning per share (EPS), sales or other financial measurements. The objective of price multiple technique is to evaluate the value of assets and compare how similar assets are priced in the market. Although stock price multiple technique is common in financial filed, studies on the application of the technique in Thailand is still limited. The present study is conducted to serve three major objectives. The first objective is to apply the technique to measure value of firms in banking sector in the Stock Exchange of Thailand. The second objective is to develop composite price multiple index to forecast equity prices. The third objective is to compare valuation accuracy of different value drivers of price multiple (i.e. EPS, Earnings Growth, Earnings Before Interest Taxes Depreciation and Amortization, Sales, Book Value and Composite Index) in forecasting equity prices. Results indicated that EPS is the most accurate value drivers of price multiple used to forecast equity price of firms in baking sector.

• 품질경영학회지
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• 제20권1호
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• pp.126-135
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• 1992

The decision making process for production planning in FMS usually involves multiple conflicting objectives and criteria. This study consists of prescreening and analytical phase. In the prescreening phase, criteria are used to reduce the set of alternative system configuration down to a small number of candidates. After this phase, a multiobjected programming model is formulated for each remainning configuration.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.110.4-110
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• 2002

In practical control area, there are many examples with multiple objectives which may conflict or compete with each other like overhead crane control, automatic train operation, and refuse incinerator plant control, etc. These kinds of control problems are called multiobjective control problems, where it is difficult to provide the desired performance with control strategies based on single-objective optimization. Because the conventional control theories usually treat the control problem as the single objective optimization problem , the methods are not adequate to treat the multiobjective control problems. Particularly, in case of large scale systems or ill-defined systems, the multiple obj..

• 산업경영시스템학회지
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• 제32권2호
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• pp.29-37
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• 2009

National R&D programs play an important role in the development of a country in this age of the knowledge economy. Since many numbers of R&D programs compete for limited resources such as national R&D budget, the R&D program evaluation problem is a challenging decision-making problem faced by decision makers that deal with R&D management. In this sense, DEA(Data Envelopment Analysis) has been regarded as one of the most widely accepted methods to measure the relative efficiency of productivity of R&D programs. DEA is a methodology to measure and to evaluate the relative efficiency of a homogeneous set of decision-making units(DMUs) in a process which uses multiple inputs to produce multiple outputs. However, the sample of the R&D programs could consist of two or more naturally occurring subsets, thus exhibiting clear signs of heterogeneity such as different objectives. In such situations, the fairness of DEA is limited, for the nature of the relative efficiency of a DMU is likely to be influenced by its membership in a particular subset of the sample. In this study, we propose a methodology AI-DEA(attainment index DEA) allowing for reflecting decision maker's subjective judgement on difference among different subsets of R&D programs which have heterogeneous objectives. This methodology combines AHP and Delphi in order to decide the attainmnet index of each DMU for each outputs, and apply them to DEA model. We illustrate the proposed approach with a pilot evaluation of 13 programs involving 6 different subsets of Korean National R&D programs and compares the results of the original DEA model and AI-DEA model.

• 한국경영과학회지
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• 제19권1호
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• pp.17-40
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• 1994

The objectives of this paper are to apply fuzzy cognitive map (FCM)- related techniques to (1) extract causal knowledge from a specific problem-domain and (2) perform a series of causal analysis in complicated decision making area. We propose a set operation-based augmentation (SOBA) algorithm to combine multiple FCMs developed by multiple experts. Based on the SOBA knowledge acquisition algorithm, we can obtain a causal knowledge base fairly representing multiple experts' knowledge about a problem domain. The causal knowledge base built by SOBA algorithm can be described as a matrix form, guaranteeing mathematically compact operation compared with a production (if-then) knowledge base. We applied out method to stock market analysis problem whichis a typical of highly unstructured problems in OR/MS fields.

• 척추신경추나의학회지
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• 제1권2호
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• pp.41-47
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• 2006

Objectives: The aim of this study is to notify incidental diagnosis of multiple myeloma during conservative treatment for lumbar disc herniation, caused by right flank pain. Methods: A 45-year-old female came to our hospital for the control of pain caused by lumbar disc hemiation L5-S1. After using Cox technique, she occured right flank pain and found out multiple fracture by bone scan. For further evaluation, she was diagnosed with multiple myeloma with bone marrow biopsy. Results and Conclusions: This case report suggests that clinicians should consider the possibility of multiple myeloma in the case of multiple fracture without trauma.

• 보건교육건강증진학회지
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• 제29권2호
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• pp.93-105
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• 2012

Objectives: The objective of the study was to examine the clustering patterns and correlates of multiple health behaviors (MHBs) in middle-aged Koreans with metabolic syndrome (MetS). Methods: Data on sociodemographics, clinical characteristics, health behaviors (vegetable intake, physical activity, cigarette smoking, and alcohol consumption), and psychological characteristics were collected by a self-reported survey and medical examination from 331 individuals with MetS. Clustering of MHBs was examined by measuring 1) the ratios of observed and expected prevalence of MHBs, and 2) the prevalence odds ratios. A binomial logistic regression were conducted. Results: Men were more likely than women to engage in multiple unhealthy behaviors. Clustering of smoking and heavy drinking was exhibited in the participants. Women with high vegetable intake were more likely to be physically inactive, and those with inadequate vegetable intake were more likely to be physically active. Those with lower self-regulation were more likely to engage in unhealthy behaviors. Conclusions: The findings support the multiple health behavior approach as opposed to the individual health behavior approach. Emphasis of self-regulation is necessary in developing multiple behavior intervention for individuals with MetS.