• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.145-152
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• 1994

This paper deals with an economic design of acelerated life test under constant stresses where failure times are exponentially distributed. In this case the optimization criterion is the information amount per unit cost. Fisher's information matrix of exponential distribution's parameters and expected cost considering fixed and variable costs are obtained. The decision variable is the censoring time in the model. In the 2-level constant stress case, it is proved that the optimal solution exists and is unique under some condition. Numerical examples are also included.

• The Journal of the Korea institute of electronic communication sciences
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• v.4 no.2
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• pp.143-151
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• 2009

This paper analyzes the state of the digital divide which targets the farmers and fishermen. They are the information alienation social class that derives from the digital divide between social members which occurs from digital economy period.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.792-798
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• 2007

In this paper, we propose a hierarchical fuzzy-rough classification method based on statistical information for maximizing the performance of pattern classification and reducing the number of rules without learning approaches such as neural network, genetic algorithm. In the proposed method, statistical information is used for extracting the partition intervals of antecedent fuzzy sets at each layer on hierarchical fuzzy-rough classification systems and rough sets are used for minimizing the number of fuzzy if-then rules which are associated with the partition intervals extracted by statistical information. To show the effectiveness of the proposed method, we compared the classification results(e.g. the classification accuracy and the number of rules) of the proposed with those of the conventional methods on the Fisher's IRIS data. From the experimental results, we can confirm the fact that the proposed method considers only statistical information of the given data is similar to the classification performance of the conventional methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.66-74
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• 2016

This study examined the effects of nursing information provision using a booklet on the patients' anxiety and uncertainty with an endoscopic submucosal dissection before the procedure, which is a non-equivalent controlled pre-post test designed study. Twenty three patients in a control group received the existing intervention, which is the general education prior to the procedure without standardized format as well as an oral explanation, and 23 patients in the experimental group received nursing information with a booklet developed by the investigator of this study. The collected data were analyzed using a ${\chi}^2$ test and Fisher's exact t-test on SPSS 21.0. The experimental group reported significantly lower anxiety (t=3.319, p=.002) and anxiety behavioral responses (t=3.508, p=.001) than those in the control group. There were no significant differences in uncertainty between the groups (t=.745, p=.460). Nursing information using the booklet is a useful nursing intervention to reduce the anxiety of patients with endoscopic submucosal dissection before the procedure.

• Journal of KIISE
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• v.42 no.2
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• pp.203-212
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• 2015

This paper proposes a traffic sign recognition method in real road environments. The video stream in driving environments has two different characteristics compared to a general object video stream. First, the number of traffic sign types is limited and their shapes are mostly simple. Second, the camera cannot take clear pictures in the road scenes since there are many illumination changes and weather conditions are continuously changing. In this paper, we improve a modified census transform(MCT) to extract features effectively from the road scenes that have many illumination changes. The extracted features are collected by histograms and are transformed by the dense descriptors into very high dimensional vectors. Then, the high dimensional descriptors are encoded into a low dimensional feature vector by Fisher-vector coding and Gaussian Mixture Model. The proposed method shows illumination invariant detection and recognition, and the performance is sufficient to detect and recognize traffic signs in real-time with high accuracy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.919-928
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• 2023

Deep learning technology is used in various fields such as self-driving cars, image creation, and virtual voice implementation, and deep learning accelerators have been developed for high-speed operation in hardware devices. However, several side channel attacks that recover secret information inside the accelerator using side-channel information generated when the deep learning accelerator operates have been recently researched. In this paper, we implemented a DNN(Deep Neural Network)-based MNIST digit classifier on a microprocessor and attempted a correlation power analysis attack to confirm that the weights of deep learning accelerator could be sufficiently recovered. In addition, to counter these power analysis attacks, we proposed a Node-CUT shuffling method that applies the principle of misalignment at the time of power measurement. It was confirmed through experiments that the proposed countermeasure can effectively defend against side-channel attacks, and that the additional calculation amount is reduced by more than 1/3 compared to using the Fisher-Yates shuffling method.

• Journal of KIISE:Software and Applications
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• v.34 no.4
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• pp.377-388
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• 2007

In this paper, we propose a multi-modal biometric system based on face, iris and fingerprint recognition system. To effectively aggregate two systems, we use statistical distribution models based on matching values for genuine and impostor, respectively. And then, We performed reveal fusion algorithms including weighted summation, Support Vector Machine(SVM), Fisher discriminant analysis, Bayesian classifier. From the various experiments, we found that the performance of multi-modal biometric system was influenced with the normalization methods and classifiers.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.2 s.308
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• pp.33-39
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• 2006

This paper presents the modified LVQ method for performance improvement of pattern classification. The proposed method uses the skewness of probability distribution between the input vectors and the reference vectors. During training, the reference vectors are closest to the input vectors using the probabilistic distribution of the input vectors, and they are positioned to approximate the decision surfaces of the theoretical Bayes classifier. In order to verify the effectiveness of the proposed method, we performed experiments on the Gaussian distribution data set, and the Fisher's IRIS data set. The experimental results show that the proposed method considerably improves on the performance of the LVQ1, LVQ2, and GLVQ.

• Research in Community and Public Health Nursing
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• v.33 no.3
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• pp.321-331
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• 2022

Purpose: This study is to establish a structural model for standard precautions compliance of nursing students. This conceptual model was based on the IMB (Information-Motivation-Behavioral skills) model of Fisher and Fisher. Methods: Data were collected from October 12 to December 1, 2020, and the subjects were nursing students from G metropolitan city and J province, and the data of a total of 334 subjects were analyzed. For data analysis, this study used the SPSS 24.0 and AMOS 24.0 programs. Results: The hypothetical model showed a good fit to the data: 𝑥²=106.46 (p<.001), 𝑥²/df=2.54, RMSEA=.07, SRMR=.04, CFI=.96, TLI=.94. It was confirmed that the variables that have a statistically significant influence on the standard precautions compliance in nursing students were in the order of self-efficacy, social support, personal attitude, and standard precautions knowledge. The model explained 48.3% of the variance in standard precautions compliance of nursing students. Conclusion: It is necessary to develop and apply various specialized extracurricular programs that can induce an individual attitude toward observing standard precautions compliance in a positive direction in relationships with teachers and peers and gain their support.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.29-36
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• 2006

This paper proposes a new algorithm of MS-EIDV (modal sensitivity-effective independence distribution vector) for determining optimal accelerometer locations (OAL) by using the Fisher Information Matrix (FIM) derived from mode-shape sensitivities. Also, the paper provides a reasonable guideline for selecting OAL which can reflect dynamic responses of a structure effectively. Since OAL should be determined with known values of structural parameters but since the parameters can be estimated by applying an inverse method such as SI (system identification) using measured response, the paper proposes a statistical method to overcome the paradox by considering the error bound of the structural parameters. To examine the proposed methods, a frequency-domain SI method has been applied. By using the identified results, the minimum necessary number of accelerometers could be selected depending on the number of target measurable modes. Through simulation studies, the results by applying EIDV method directly using the information of mode shapes were compared with those by applying the proposed MS-EIDV.