• 근관절건강학회지
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• 제3권1호
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• pp.63-89
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• 1996

This study has been done for the purpose of determining whether the positive association between social support and depression is attributable to an overall beneficial effect of support(direct effect) or to a process of support protecting persons from adverse effects of stressors such as life events, pain or physical disability (buffering effect). The sample consisted of 214 patients who were identified as the rheumatoid arthritis. The instruments used in this study were Depression Scale(CES-D), Perceived Social Support Scale, Life Events Questionnaire, AIMS Pain Scale, and Physical Disability Scale. The data were analysed by the use of t-test, ANOVA, Pearson Correlation Coefficient and Stepwise Multiple Regression. The results of this study are summerized as follows : 1. The 1st hypothesis, "The higher the life events degree, the higher the depression degree" was supported(r=.49, P=.0001). 2. The 2nd hypothesis, "The higher the pain degree, the higher the depression degree" was supported(r=.44, P=.0001). 3. The 3rd hypothesis, "The higher the physical disability degree, the higher the depression degree" was supported (r=.46, P=.0001). 4. The 4th hypothesis, "The higher the social support degree, the lower the depression degree" was supported(F=84.52, P=.0001). 5. The 5th hypothesis, "There will be different in the relationship between the degrees of life events and depression according to social support degree" was rejected (F=.29, P=.5928). 6. The 6th hypothesis, "There will be different in the relationship between the degrees of pain and depression according to social support degree" was supported (F=3.19, P=.0755). 7. The 7th hypothesis, "There will be different in the relationship between the degrees of physical disability and depression according to social support degree" was supported(F=5.69, P=.018). 8. The predictive variables for depression were the degrees for social support, life events, pain, and physical disability. 9. The depression degree showed a inverse correlation with social support degree (r=-.56, p=.0001). The social support degree showed a inverse correlation with the degrees of life events(r=-.22, p=.0007), pain(r=-.18, p=.0069) and physical disability(r=-.15, p=.0293). 10. The depression degree showed significant differences in the variables of sex (t=2.26, p=.025), educational level(r=.189, P=.006) and the number of treatment method (r=.201, P=.003). In conclusion, it was found that social support had the direct effect on depression and the buffering effect in each relationship between degrees of pain or physical disability and depression in patients with rheumatoid arthritis. So the researcher thinks that it is effective that nurses should provide these patients with social support to reduce depression in cases of having severe pain or physical disability.

• 한국정보통신학회논문지
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• 제13권4호
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• pp.700-713
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• 2009

데이터마이닝 분야에서 기존의 분류알고리즘들은 보다 적은 컴퓨팅 자원을 이용하여 보다 빨리 분류모형을 생성하고자 하는 효율성 중심의 연구가 주를 이루었다. 본 논문에서는 분류알고리즘의 효율성을 추구할 뿐 아니라 온톨로지 자동생성이나 비즈니스 환경 등 각 응용분야에 적합한 유효한 분류규칙을 보다 많이 생성 할 수 있는 효과성도 동시 에 추구하였다. 이를 위하여 지지도와 신뢰도의 가중치가 적용된 가중치 적용함수를 제안하였고 이 함수의 성질들을 이론적으로 규명하였다. 가중치 적용함수를 사용하면서 새로운 분리 기준 설정 방법을 제안하였고 또한 새로운 분류알고리즘을 제안하였다. 제안한 알고리즘의 성능평가 결과 기존의 우수한 알고리즘보다 보다 많은 유효한 분류규칙들을 보다 신속하게 생성함을 알 수 있었다.

• International Journal of CAD/CAM
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• 제6권1호
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• pp.51-58
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• 2006

In rapid prototyping, the optimal part orientation during fabrication is critical as it can improve part accuracy, minimize the requirement for supports and reduce the production time. Through investigating the geometric issues of STL model and process planning of RPM, This paper establishes optimizing model based on the considerations of staircase effect, support area and production time. The general satisfactory degree function is constructed employing the multi-objective optimization theory based on the general satisfactory degree principle. The best part-building orientation is obtained by solving the function employing generic algorithm. Experiment shows that the methods can effective resolve the part-building orientation in RP.

• Structural Engineering and Mechanics
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• 제63권1호
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• pp.115-124
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• 2017

In this paper, a different technique to predict the effects of soil-structure interaction (SSI) on seismic response of building systems is investigated. The technique use a machine learning algorithm called Support Vector Regression (SVR) with technical and analytical results as input features. Normally, the effects of SSI on seismic response of existing building systems can be identified by different types of large data sets. Therefore, predicting and estimating the seismic response of building is a difficult task. It is possible to approximate a real valued function of the seismic response and make accurate investing choices regarding the design of building system and reduce the risk involved, by giving the right experimental and/or numerical data to a machine learning regression, such as SVR. The seismic response of both single-degree-of-freedom system and six-storey RC frame which can be represent of a broad range of existing structures, is estimated using proposed SVR model, while allowing flexibility of the soil-foundation system and SSI effects. The seismic response of both single-degree-of-freedom system and six-storey RC frame which can be represent of a broad range of existing structures, is estimated using proposed SVR model, while allowing flexibility of the soil-foundation system and SSI effects. The results show that the performance of the technique can be predicted by reducing the number of real data input features. Further, performance enhancement was achieved by optimizing the RBF kernel and SVR parameters through grid search.

• ETRI Journal
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• 제46권4호
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• pp.604-618
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• 2024

In wireless sensor network (WSN) monitoring systems, redundant data from sluggish environmental changes and overlapping sensing ranges can increase the volume of data sent by nodes, degrade the efficiency of information collection, and lead to the death of sensor nodes. To reduce the energy consumption of sensor nodes and prolong the life of WSNs, this study proposes a dual layer intracluster data fusion scheme based on ring buffer. To reduce redundant data and temporary anomalous data while guaranteeing the temporal coherence of data, the source nodes employ a binarized similarity function and sliding quartile detection based on the ring buffer. Based on the improved support degree function of weighted Pearson distance, the cluster head node performs a weighted fusion on the data received from the source nodes. Experimental results reveal that the scheme proposed in this study has clear advantages in three aspects: the number of remaining nodes, residual energy, and the number of packets transmitted. The data fusion of the proposed scheme is confined to the data fusion of the same attribute environment parameters.

• Wind and Structures
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• 제8권5호
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• pp.343-356
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• 2005

Overhead sign support structures number in the tens of thousands throughout the trunk-line roadways in the United States. A recent two-phase study sponsored by the National Cooperative Highway Research Program resulted in the most significant changes to the AASHTO design specifications for sign support structures to date. The driving factor for these substantial changes was fatigue related cracks and some recent failures. This paper presents the method and results of a subsequent study sponsored by the Michigan Department of Transportation (MDOT) to develop a relative performance-based procedure to rank overhead sign support structures around the United States based on a linear combination of their expected fatigue life and an approximate measure of cost. This was accomplished by coupling a random vibrations approach with six degree-of-freedom linear dynamic models for fatigue life estimation. Approximate cost was modeled as the product of the steel weight and a constructability factor. An objective function was developed and used to rank selected steel sign support structures from around the country with the goal of maximizing the objective function. Although a purely relative approach, the ranking procedure was found to be efficient and provided the decision support necessary to MDOT.

• 대한간호학회지
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• 제20권1호
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• pp.88-117
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• 1990

The purposes of this study are to delineate a profile of the state of a stroke patient's adaptation at 3 months after hospitalization and to explore the relationship between the level of adaptation and the variables which influence the adaptation of hemiplegic patients. To these ends, theoretical framework was derived basically from the stress adaptation model. The basic assumption underlying the level of adaptation is influenced by the presenting focal, contextual and residual stimuli. This group of stimuli is further operationalized and represented by a perception of stress. which is the perceived effect of the disability and by the mediating variables such as sociodemographic factors as an external conditioning variables and perceived social support and hardiness personality characteristics as an internal intervening variables. The dependent varibales in this study is the level of physical, psychological and social adaptation and is hypothesized to be a function of the interaction between 3 sets of variables namely, the perceived disability effect, external conditioning variables and internal intevening varibles. A total of fourty three subjects from 3 general hospitals in Seoul were observed and interviewed with the aid of 7 structured instruments. The data were collected twice on each subject : first at the pre-discharge period arid at 3 months post-discharge from hospital for the second time. The study was carried out for the period from February to August, 1988. The instruments used for the study include 4 existing scales and 3 scales developed by the researcher for this study. They are : 1) The ADL dependency scale and the scale of the clinical physical functions for the assessment of physical adaptation. 2) the SDS(self report of depression) to measure the level of psychological adaptation. 3) The scale for the amount of social activities for the measurement of the level of social adaptation. 4) The scale for the perceived effect of disability for the measurement of the focal stimuli. 5) The health related hardiness scale and the perceived interpersonal support self evaluation list(ISEL) for the measurement of the hardiness personality character and the perceived social support. The data obtained were analyzed using percentage, oneway ANOVA, Pearson coefficients correlation and stepwise multiple regression. The findings provide valuable information about the present level of physical adaptation at 3 months after discharge. The patient revealed a decreased ADL dependency and lowered limitation of physical function as compared with pre - discharge state. Psycholcgically, the average degree of depression at follow up was within normal range of depression. Socially, the amount of social activities was very low. The one way ANOVA and the correlational analysis revealed the relationship between the 3 sets of variables and the adaptation level as follows : 1) The perceived disability effect was related to the degree of the depression and the amount of social activities but was not related to the physical adaptation. 2) Among the sociodemographic variables, sex and education were related to the difference of ADL dependency and the change of physical function. These factors indicate that women more than men and educated more than the less educated were found more independent. The education was also related to the degree of depression suggesting that the higher the educational level, the more well adapted the patients were both physically and psychologically. Age, marital status and job state were not found to be related to the patient's adaptation level. 3) Among the internal intervening variables, the health related hardiness characteristic was related to the differences of ADL dependency, physical functions and the social activities, indicating that the higher the hardiness character the higher the level of physical and social adaptation. 4) The perceived social support, another internal intervening variable, was related to the degree of depression and the social activities. This data suggest that the higher the perception of social support, the better adapted the patients were psychogically and socially. In summarizing the results of the correlational analysis, the level of physical adaptation was influenced by sex, the years of education and the hardiness character. The level of psychological adaptation was influenced by the years of education, the perceived disability effect and the perceived social support. And the level of social adaptation was influenced by the perceived disability effect, the hardiness character and the perceived social support. The stepwise multiple regression analysis shows findings as follows : 1) The most important factor to explain the difference of ADL dependency was sex, indicating females were more independent than males. 2) The most important factor to explain the difference of physical function and the degree of depression was the patient's education level. 3) The strongest explaining factor for the amount of social activities was perceived self esteem(one of the subconcepts of perceived social support). Thus the most important factors influencing the level of adaptation were found to be sex, education, the hardiness character and self esteem. From the above findings, the significance of this study can be delineated as follows : 1) Corroboration of the assumed relationship between the various variables and the adaptation level as suggested in the conceptual model. 2) Support for the feasibility of the cognitive approach for nursing intervention such as hardness character training, counselling and teaching for self-care in the chronic patients.

• 한국정보시스템학회지:정보시스템연구
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• 제7권1호
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• pp.99-128
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• 1998

The increasing importance of IT rose to the top of list of marketing managers' key concerns and IT has been used widely in performing various marketing activities and decisions. However, little was known about how to employ IT in various marketing activities and how to use IT as a strategic marketing means. Also, comprehensive empirical studies have rarely been conducted. This study examines the effectiveness of integrative use of marketing and IT. More specifically, this study attempts to identify the factors that influence the effectiveness of marketing information systems. The manufacturing firms listed in the Korean Stock Market were surveyed. the major findings of this study are as follows. First, the variables of organizational characteristics such as formalization of decision making cooperation between marketing function and IS function, and degree of decentralization were significantly related to the success of marketing information systems. The variables of user highly associated with the success of marketing information systems. Second, it was also found that the support capability of marketing information systems is the major factor of the effectiveness of marketing information systems. Third, the variables marketing function and IS function, and ratio of export sales to total sales were three variables such as marketing knowledge of marketing managers, cooperation were the main factors to affect the users' satisfaction with the information system. These results imply that, in order to increase the effectiveness of marketing information systems, a firm should enhance a cooperation between marketing function and IS function, diversify the support capability of IS, and strengthen the computer mind and computer knowledge of end-uses.

• 재활간호학회지
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• 제4권1호
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• pp.58-72
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• 2001

A Cerebrovascular accident(CVA), or Stroke is a medical emergency that occurred when the blood supply to the brain is interrupted or blocked. The stroke causes physical function disorder due to hemiparalysis and emotional disorder. Also the stroke patients experience helplessness, powerlessness, sense of alienation and loss of hope. These feelings make the rehabilitation difficult because they lose the will of life. The purpose of this study is to identify the correlation between perceived social support and hope of stroke survivors. The subjects for this study were 100 out-patients with stroke in one general hospital and oriental medicine hospital located in Mokpo. The data were analysed by frequency, t-test, ANOVA. Duncan test, Pearson's correlation, using the SPSS WIN 9.0 program. Data were collected from July 11 to September 9, 2000, using a structured questionnaire. The instruments used for this study : The social support scale developed by Park, Ji-won(1985) and the hope scale developed by Miller(1988). The results were as follows. 1. It was found that the higher the degree of perceived social support, the higher the degree of hope(r=.726, p=.000). Therefore hypothesis was supported. 2. The mean score of perceived social support was 77.8(SD=21.0) with a score range from 27.0 to 104.0. 3. The mean score of perceived hope was 117.0(SD=25.7) with a score range from 57.0 to 160.0. 4. The level of social support depending on general characteristics were significantly different in variables such as marital status(t=3.131, p=.010). degree of income satisfaction(F=16.027, p=.000). 5. The level of hope depending on general characteristics were significantly different in variables such as marital status(t=2.681, p=.040). current job(t=-2.055, p=.043) degree of income, satisfaction(F=11.363, p=.000). For these subjects, there was a significant relationship between social support and hope. The stroke survivors need social support to inspire their hope. Nurses should plan interventions to enhance social support for patients with stroke. The above results may be used as the basic data to seek more efficient way of elevating nursing practice and rehabilitation for the patients with stroke.

• International journal of advanced smart convergence
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• 제8권1호
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• pp.133-140
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• 2019

In this paper, we present an algorithm for adjusting degree of belief for consistency on the evidence dependency network where various sets of evidence support different sets of hypotheses. It is common for experts to assign higher degree of belief to a hypothesis when there is more evidence over the hypothesis. Human expert without knowledge of uncertainty handling may not be able to cope with how evidence is combined to produce the anticipated belief value. Belief in a hypothesis changes as a series of evidence is known to be true. In non-monotonic reasoning environments, the belief retraction method is needed to clearly deal with uncertain situations. We create evidence dependency network from rules and apply the evidence retraction algorithm to refine belief values on the hypothesis set. We also introduce negative belief values to reflect the reverse effect of evidence combination.