• Journal of Korean Academy of Nursing
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• v.53 no.2
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• pp.222-235
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• 2023

Purpose: The aim of this study was to identify the factors explaining protective behaviors against radiation exposure in perioperative nurses based on the theory of planned behavior. Methods: This was a cross-sectional study. A total of 229 perioperative nurses participated between October 3 and October 20, 2021. Data were analyzed using SPSS/WIN 23.0 and AMOS 23.0 software. The three exogenous variables (attitude toward radiation protective behaviors, subjective norm, and perceived behavioral control) and two endogenous variables (radiation protective intention and radiation protective behaviors) were surveyed. Results: The hypothetical model fit the data (χ²/df = 1.18, SRMR = .02, TLI = .98, CFI = .99, RMSEA = .03). Radiation protective intention (β = .24, p = .001) and attitude toward radiation protective behaviors (β = .32, p = .002) had direct effects on radiation protective behaviors. Subjective norm (β = .43, p = .002) and perceived behavior control (β = .24, p = .003) had direct effects on radiation protective intention, which explained 38.0% of the variance. Subjective norm (β = .10, p = .001) and perceived behavior control (β = .06, p = .002) had indirect effects via radiation protective intention on radiation protective behaviors. Attitude toward radiation protective behaviors, subjective norm, and perceived behavioral control were the significant factors explaining 49.0% of the variance in radiation protective behaviors. Conclusion: This study shows that the theory of planned behavior can be used to effectively predict radiation protective behaviors in perioperative nurses. Radiation safety guidelines or education programs to enhance perioperative nurses' protective behaviors should focus on radiation protective intention, attitude toward radiation protective behaviors, subjective norm, and perceived behavioral control.

• Communications of the Korean Mathematical Society
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• v.9 no.2
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• pp.303-315
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• 1994

Let X be a real Banach space with norm ∥ㆍ∥. Let T > 0, r ≥a be fixed constants. We denote by L/sup p/ the usual L/sup p/( -r, 0; X) with norm ∥ㆍ∥/sub p/ for 1 ≤p < ∞. Our object is to study the existence of solutions of nonlinear functional evolution equations of the type (FDE) x'(t) ＋ A(t)x(t) = G(t, x/sub t/), 0 ≤t ≤T, x/sub 0/ = ø.(omitted)

• Journal of the Korean Society for information Management
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• v.12 no.1
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• pp.87-97
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• 1995

Boolean retrieval systems have been most widely used in the area of information retrieval due to easy implementation and efficient retrieval. Conventional Boolean retrieval systems. however, cannot rank retrieved documents in decreasing order of query-document similarities because they cannot compute similarity coefficients between queries and documents. Extended Boolean models such as fuzzy set. Waller-Kraft, Paice, P-Norm and Infinite-One have been developed to provide the document ranking facility. In extended Boolean models, the formulas evaluating Boolean operators AND and OR are an important component to affect the quality of document ranking. In this paper we present mathematical properties of the formulas, and analyse their effect on retrieval effectiveness. Our analyses show that P-Norm is the most suitable for achieving high retrieval effectiveness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.3
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• pp.597-604
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• 2001

In conventional boolean retrieval systems, document ranking is not supported and similarity coefficients cannot be computed between queries and documents. The MMM, Paice and P-norm models have been proposed in the past to support the ranking facility for boolean retrieval systems. They have common properties of interpreting boolean operators softly. In this paper we propose a new soft evaluation method for Information retrieval using query splitting relevance feedback model. We also show through performance comparison that query splitting relevance feedback(QSRF) is more efficient and effective than MMM, Paice and P-norm.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.745-751
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• 2004

In conventional boolean retrieval systems, document ranking is not supported and similarity coefficients cannot be computed between queries and documents. The MMM(Max and Min Model), Paice and P-norm models have been proposed in the past to support the ranking facility for boolean retrieval systems. They have common properties of interpreting boolean operators softly In this paper we propose a new soft evaluation method for web Information retrieval using local context analysis feedback model. We also show through performance comparison that local contort analysis feedback is more efficient and effective than MMM, Paice and P-norm.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.252-257
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• 2001

In conventional boolean retrieval systems, document ranking is not supported and similarity coefficients cannot be computed between queries and documents. The MMM, Paice and P-norm models have been proposed in the past to support the ranking facility for boolean retrieval systems. They have common properties of interpreting boolean operators softly. In this paper we propose a new soft evaluation method for Information retrieval using query splitting relevance feedback model. We also show through performance comparison that query splitting relevance feedback(QSRF) is more efficient and effective than MMM, Paice and P-norm.

• Bulletin of the Korean Mathematical Society
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• v.52 no.5
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• pp.1729-1735
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• 2015

It is known that the partial sum of the Taylor series of an holomorphic function of one complex variable converges in norm on $H^p(\mathbb{D})$ for 1 < p < ${\infty}$. In this paper, we consider various type of partial sums of a holomorphic function of several variables which also converge in norm on $H^p(\mathbb{B}_n)$ for 1 < p < ${\infty}$. For the partial sums in several variable cases, some variables could be chosen slowly (fastly) relative to other variables. We prove that in any cases the partial sum converges to the original function, regardlessly how slowly (fastly) some variables are taken.

• Honam Mathematical Journal
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• v.25 no.1
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• pp.95-115
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• 2003

Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p{\geq}4)$ under the quadratic loss, based on a sample $X_1,\;{\cdots}X_n$. We find an optimal decision rule within the class of Lindley type decision rules which shrink the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm $||{\theta}-{\bar{\theta}}1||$ is known, where ${\bar{\theta}}=(1/p)\sum_{i=1}^p{\theta}_i$ and 1 is the column vector of ones. When the norm is restricted to a known interval, typically no optimal Lindley type rule exists but we characterize a minimal complete class within the class of Lindley type decision rules. We also characterize the subclass of Lindley type decision rules that dominate the sample mean.

• Journal of the Korean Society for information Management
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• v.16 no.1
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• pp.7-30
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• 1999

This study is to develop effective document ranking algorithms in the P-norm retrieval system which can be implemented to the Boolean retrieval system without major difficulties by using non-statistical term weights based on document structure. Also, it is to enhance the performance by introducing the rank adjustment process which rearranges the ranks of retrieved documents according to the similarity between the top ranked documents and the rest of them. Of the non-statistical term weight algorithms, this study uses field weight and term pair distance weight. In the rank adjustment process, five retrieval experiments were performed, ranging between the case of using one record for the similarity measurement and the case of using first five records. It is proved that non-statistical term weights are highly effective and the rank adjustment process enhance the performance further.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.21 no.1
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• pp.48-56
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• 2014

Purpose: This study was done to identify factors based on the theory of planned behavior that predict smoking cessation in elderly smokers following a stroke. Method: Between March and May 2013, data related to intention, attitude toward the behavior, subjective norm, and perceived behavioral control, were collected through questionnaire from 223 elders who smoked and who had a stroke. Data analysis was performed using PASW (SPSS) 18.0 program, and included t-test, one-way ANOVA, Pearson correlation coefficients, and multiple stepwise liner regression analysis. Results: Results showed a positive correlation between intention and attitude toward the behavior (r=.494, p<.001), subjective norm (r=.390, p<.001), and perceived behavioral control (r=.189, p=.005). These variables such as perceived behavior control, subjective norm, number of cigarettes per day, and usefulness of quitting smoking explained 50% of intention to quit smoking. Conclusion: The results of this study indicate that there is a need to develop smoking cessation nursing strategies for elderly smokers following a stroke in order to provide effective counseling on subjective norm and perceived behavioral control.