• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4502-4518
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• 2015

Fisher linear discriminant analysis (LDA) is one of the most popular projection techniques for feature extraction and has been widely applied in face recognition. However, it cannot be used when encountering the single sample per person problem (SSPP) because the intra-class variations cannot be evaluated. In this paper, we propose a novel method called local similarity based linear discriminant analysis (LS_LDA) to solve this problem. Motivated by the "divide-conquer" strategy, we first divide the face into local blocks, and classify each local block, and then integrate all the classification results to make final decision. To make LDA feasible for SSPP problem, we further divide each block into overlapped patches and assume that these patches are from the same class. To improve the robustness of LS_LDA to outliers, we further propose local similarity based median discriminant analysis (LS_MDA), which uses class median vector to estimate the class population mean in LDA modeling. Experimental results on three popular databases show that our methods not only generalize well SSPP problem but also have strong robustness to expression, illumination, occlusion and time variation.

• Smart Structures and Systems
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• v.25 no.2
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• pp.169-181
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• 2020

Sensor placement is a crucial aspect of bridge health monitoring (BHM) dedicated to accurately estimate and locate structural damages. In addressing this goal, a sensor placement framework based on the deflection influence line (DIL) analysis is here proposed, for the optimal design of damage detection-oriented BHM system. In order to improve damage detection accuracy, we explore the change of global stiffness matrix, damage coefficient matrix and DIL vector caused by structural damage, and thus develop a novel sensor placement framework based on the Fisher information matrix. Our approach seeks to determine the contribution of each sensing node to damage detection, and adopts a distance correction coefficient to eliminate the information redundancy among sensors. The proposed damage detection-oriented optimal sensor placement (OSP) method is verified by two examples: (1) a numerically simulated three-span continuous beam, and (2) the Pinghu bridge which has existing real damage conditions. These two examples verify the performance of the distance corrected damage sensitivity of influence line (DSIL) method in significantly higher contribution to damage detection and lower information redundancy, and demonstrate the proposed OSP framework can be potentially employed in BHM practices.

• The Korean Journal of Rehabilitation Nursing
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• v.17 no.1
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• pp.48-55
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• 2014

Purpose: In this study, we attempted to provide an evidence for the effects of meridian acupressure on relieving and preventing constipation in the institutionalized elderly. Methods: The research design was a non-equivalent control group, non-synchronized design. The subjects consisted of 31 institutionalized elderly (experimental group: 16, control group: 15). The experimental group was given meridian acupressure for 10 minutes daily for 2 weeks. The data was analyzed by the ${\chi}^2$-test, Fisher's exact test, t-test and repeated measures ANOVA. Results: The number of bowel movements per week of the experimental and control group performed meridian acupressure verified by repeated-measures analysis of variance revealed that interaction existed between the meridian acupressure availability and the measurement point (F=98.183, p<.001). Repeated measures analysis of variance to compare the changes in Bristol stool form scale scores of the experimental and control group performed meridian acupressure revealed that interaction existed between the meridian acupressure availability and the measurement point (F=48.896, p<.001). Conclusion: The results of this study show the meridian acupressure is a useful nursing intervention on constipation in the institutionalized elderly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.1
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• pp.5-21
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• 2008

In order to securely transmit multicast data packets in a mobile environment where frequent join/leave events are a characteristic of the environment, there is a need for a new secure and efficient group key management solution. We propose a secure group key generation/distribution solution providing scalability and reliability. Using this solution, when a mobile node, which is in a multicast session, enters a new domain, the agent of the domain joins the multicast session and coordinates its data packets with the mobile node. The agent encrypts and transmits subsequent data packets to the mobile node, using a local one-time pad key. This key is generated with FI sequences, enabling the mobile node to regenerate the same data packet, based on the information sent by the agent. Our performance analysis demonstrates that the proposed solution can significantly reduce the number of key generations and distributions, when it is applied to the hierarchical mobile IPv6 network.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.9-15
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• 2011

In this paper, we design and implement of gate management system by face recognition using smart phone. We investigate various algorithms for face recognition on smart phones. First step in any face recognition system is face detection. We investigated algorithms like color segmentation, template matching etc. for face detection, and Eigen & Fisher face for face recognition. The algorithms have been first profiled in MATLAB and then implemented on the Android phone. While implementing the algorithms, we made a tradeoff between accuracy and computational complexity of the algorithm mainly because we are implementing the face recognition system on a smart phone with limited hardware capabilities.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.1
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• pp.87-101
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• 2000

End-User Computing(EUC) is a rapidly growing phenomenon in organizations As EUC gets to be a major segment of information systems, it becomes more important to manage EUC effectively. This paper focuses on developing an integrative framework of EUC management in the contingent perspective. The characterstic of task for which EUC is implemented was considered as a contingent variable. Based on systematic review of previous research on success factors of EUC implementation, three generic variables for EUC management were identified theoretically, which were support, promotion and control. The contingent relationships between these three EUC management variables and EUC performance were reasoned and four hypotheses concerning these relationships were derived. A field study was undertaken to test the hypotheses. Data were collected from 83 End-Users belonging to Korean business organizations. Correlation analyses and Fisher's Z tests were employed to test the hypotheses. The results supported the hypotheses for the most part and gave implications and future research directions for the management for EUC.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.117-125
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• 2015

In this paper, we propose a classification algorithm based on the obtained EEG(Electroencephalogram) signal for the control of 'left' and 'right' turnings of which a driving system composed of EEG sensor, Labview, DAQ, Matlab and driving robot. The proposed algorithm uses features extracted from frequency band information obtained by DWT (Discrete Wavelet Transform) and selects features of high discrimination by using Fisher score. We, also propose the number of feature vectors for the best classification performance by using SVM(Support Vector Machine) classifier and propose a decision pending algorithm based on MLD (Maximum Likelihood Decision) to prevent malfunction due to misclassification. The selected four feature vectors for the proposed algorithm are the mean of absolute value of voltage and the standard deviation of d5(2-4Hz) and d2(16-32Hz) frequency bands of P8 channel according to the international standard electrode placement method. By using the SVM classifier, we obtained 98.75% accuracy and 1.25% error rate. Also, when we specify error probability of 70% for decision pending, we obtained 95.63% accuracy and 0% error rate by using the proposed decision pending algorithm.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2907-2915
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• 2018

Journal of the Korean Data Analysis Society founded in 1998 has played the role of a major application journal. In this study, we checked the objective of this journal by checking the abstracts for 10 years. Abstract data was crawled from the online journal site (kdas.jems.or.kr) and analyzed by topic model. As a result, we found 18 topics from 2680 abstracts that had several contents, for example, nursing, marketing, economics, regression, factor analysis, data mining and statistical inferences. Topic1 (regression) is most frequent with 460 documents and we found the usefulness of regression in the applied science area. We confirmed the significant 10 association rules using by Fisher's exact test. Also, for exploring the trend of topics, we conducted the topic analysis for two periods which are 2006-2011 period and 2012-2016 period. We found that the control study was more frequent than survey study over time and regression and factor analysis were frequent regardless of time.

• The Journal of the Acoustical Society of Korea
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• v.26 no.3E
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• pp.104-110
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• 2007

As the exploration of the seabed is extended ever further, automated recognition and classification of sonar images become increasingly important. However, most of the methods ignore the directional information and its effect on the image textures produced. To deal with this problem, we apply 2D Gabor filters to extract the features of sonar images. The filters are designed with constrained parameters to reduce the complexity and to improve the calculation efficiency. Meanwhile, at each orientation, the optimal Gabor filter parameters will be selected with the help of bandwidth parameters based on the Fisher criterion. This method can overcome some disadvantages of the traditional approaches of extracting texture features, and improve the recognition rate effectively.

• Journal of the Korean Mathematical Society
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• v.35 no.3
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• pp.755-764
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• 1998

The least informative distributions minimizing Fisher information for location are obtained in the classes of continuously differentiable and piece-wise continuously differentiable densities with the additional restrictions on their values at the median and mode of population in the point and interval forms. The structure of these optimal solutions depends both on the assumptions of smoothness and form of characterizing restrictions of the class of distributions: in the class of continuously differentiable densities, the least informative distributions are finite and have the cosine-type form, and, in the class of piece-wise continuously differentiable densities, the least informative densities have exponential-type tails, the Laplace density in particular. The dependence of optimal solutions on the assumptions of symmetry is also analyzed.