KSII Transactions on Internet and Information Systems (TIIS)
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v.12
no.10
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pp.5015-5038
/
2018
In this paper, a novel spectral-spatial joint sparse representation algorithm for hyperspectral image classification is proposed based on multi-layer superpixels in various scales. Superpixels of various scales can provide complete yet redundant correlated information of the class attribute for test pixels. Therefore, we design a joint sparse model for a test pixel by sampling similar pixels from its corresponding superpixels combinations. Firstly, multi-layer superpixels are extracted on the false color image of the HSI data by principal components analysis model. Secondly, a group of discriminative sampling pixels are exploited as reconstruction matrix of test pixel which can be jointly represented by the structured dictionary and recovered sparse coefficients. Thirdly, the orthogonal matching pursuit strategy is employed for estimating sparse vector for the test pixel. In each iteration, the approximation can be computed from the dictionary and corresponding sparse vector. Finally, the class label of test pixel can be directly determined with minimum reconstruction error between the reconstruction matrix and its approximation. The advantages of this algorithm lie in the development of complete neighborhood and homogeneous pixels to share a common sparsity pattern, and it is able to achieve more flexible joint sparse coding of spectral-spatial information. Experimental results on three real hyperspectral datasets show that the proposed joint sparse model can achieve better performance than a series of excellent sparse classification methods and superpixels-based classification methods.
In order to consider high-order effects on the actual limit state function, a new response surface method is proposed for structural reliability analysis by the use of high-order approximation concept in this study. Hermite polynomials are used to determine the highest orders of input random variables, and the sampling points for the determination of highest orders are located on Gaussian points of Gauss-Hermite integration. The cross terms between two random variables, only in case that their corresponding percent contributions to the total variation of limit state function are significant, will be added to the response surface function to improve the approximation accuracy. As a result, significant reduction in computational cost is achieved with this strategy. Due to the addition of cross terms, the additional sampling points, laid on two-dimensional Gaussian points off axis on the plane of two significant variables, are required to determine the coefficients of the approximated limit state function. All available sampling points are employed to construct the final response surface function. Then, Monte Carlo Simulation is carried out on the final approximation response surface function to estimate the failure probability. Due to the use of high order polynomial, the proposed method is more accurate than the traditional second-order or linear response surface method. It also provides much more efficient solutions than the available high-order response surface method with less loss in accuracy. The efficiency and the accuracy of the proposed method compared with those of various response surface methods available are illustrated by five numerical examples.
Kim, Eu-Tteum;Pak, Son-Il;Park, Choi-Kyu;Kweon, Chang-Hee
Korean Journal of Veterinary Research
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v.47
no.4
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pp.417-423
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2007
Serological surveillance programs in animal populations are becoming increasingly important to estimate prevalence of a specific disease and subsequently to document disease-free status in a region or a country. For these purposes, the programs need to be based on both theoretical and economical aspects from the designing phase. From Aujeszky's disease (AD)-eradication program point of view, group of animals (aggregates, herds) not individual animal is the more important sampling unit of concern. In this study the authors therefore attempted to compute an appropriate sample size tailored to a current surveillance program against AD, assuming that the goal of this program is either herd-level prevalence estimation or documentation of AD-freedom. For prevalence estimation, assuming a finite population with imperfect sensitivity (Se) and specificity (Sp) of ELISA kit for AD diagnosis, the number of herds present, expected herd prevalence, and desired accuracy for a certain level of confidence, sample size was estimated at herd-level in the first stage and individual animal-level in the second stage. A two-stage sampling design was used to calculate a sample size to indicate AD-freedom. In this instance, the computation was based on the possible detection of a predetermined prevalence at a certain herd-level Se and Sp. This study indicated that the sample size varied with predetermined confidence, tolerance, Se and Sp at herd- and animal-level, and within- and among-herd prevalence. In general, smaller sample size was required to estimate AD prevalence than to document of AD-freedom. Compared to individual-based samples, two-stage sampling strategy requires a larger sample size to show disease-freedom. Statistical considerations including herd-level test characteristics when designing surveillance program also are further discussed.
Animal disease surveillance system, defined as the continuous investigation of a given population to detect the occurrence of disease or infection for control purposes, has been key roles to assess the health status of an animal population and, more recently, in international trade of animal and animal products with regard to risk assessment. Especially, for a system aiming to determine whether or not a disease is present in a population sensitivity of the system should be maintained high enough not to miss an infected animal. Therefore, when planning the implementation of surveillance system a number of factors that affecting surveillance sensitivity should be taken into account. Of these parameters sample size is of important, and different approaches are used to calculate sample size, usually depending on the objective of surveillance systems. The purpose of this study was to evaluate the sensitivity of the current national serological surveillance programs for four selected bovine diseases assuming a specified sampling plan, to examine factors affecting the probability of detection, and to provide sample sizes required for achieving surveillance goal of detecting at least an infection in a given population. Our results showed that, for example, detecting low level of prevalence (0.2% for bovine tuberculosis) requires selection of all animals per typical Korean cattle farm (n = 17), and thus risk-based target surveillance for high risk groups can be an alternative strategy to increase sensitivity while not increasing overall sampling efforts. The minimum sample size required for detecting at least one positive animal was sharply increased as the disease prevalence is low. More importantly, high reliability of prevalence estimation was expected with increased sampling fraction even when zero-infected animal was identified. The effect of sample size is also discussed in terms of the maximum prevalence when zero-infected animals were identified and on the probability of failure to detect an infection. We suggest that for many serological surveillance systems, diagnostic performance of the testing method, sample size, prevalence, population size, and statistical confidence need to be considered to correctly interpret results of the system.
Journal of the Korea Academia-Industrial cooperation Society
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v.19
no.10
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pp.55-63
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2018
This study was intended to identify path structures through pathway analysis with an emphasis on the cognitive elements that influence the acculturative stress of marriage-based immigrant women. The results of the study were designed to establish a foundation for practical measures and policies to support marriage-based immigrant women to adjust their lives in the culture. This study has established research model on the path structure according to the psychological stress theory as to how social support, coping strategy, and acculturative attitude recognized as a cognitive element of marriage-based immigrant women on the acculturative stress and implement practical verification. In addition, control variables for the use of ages, education level, period of marriage, and income level of socio-demographic variables were analyzed. To obtain data for the study, convenience sampling and snowball sampling of marriage-based immigrant women that resided in the area of C and J were conducted simultaneously through surveys and applied to the analysis of 204 cases. Analysis of the path structure of influence of social support, coping strategies, and acculturative attitudes that were perceived as a cognitive element of marriage-based immigrant women influencing acculturative stress revealed that these factors were specifically weighted towards acculturative. Moreover, comprehensive acculturative attitude was identified as a crucial variable reducing the effects of acculturative stress during the acculturative procedures of marriage-based immigrant women. This assumes that establishing and performing policies supporting co-existence of homeland cultures of marriage-based immigrant women and Korean cultures might be an efficient action for dealing with acculturative stress rather than forcing them to adjust to Korean culture.
In this paper, position and speed control algorithm of LSM (Linear Stepping Motor) using general-purpose PCI I/O board is discussed. The main purpose of this paper is to show that LSM controller can be established on the non real time operating system such as Microsoft Win2000 under the assumption that thread priority strategy is well designed. We can guarantee sampling interval less than 5msec based on the Pentium III microprocessor. Therefore this kind of LSM controller development environment makes shorten the prior research period needed to verify the validness of the proposed control strategy. We also introduce the tool of the real-time windows target system of matlab, which also makes shorten the prior research period. The main focus of this paper is on developing general purpose NT device driver which can drive the general purpose PCI board and applying it for implementing the hardware interface for 2- axis linear stepping motor control. From the experimental results show that the developed LSM controller guarantee 2 micrometer resolution in position control with 10cm/sec moving speed
Journal of Institute of Control, Robotics and Systems
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v.22
no.2
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pp.104-109
/
2016
In this paper, a localization method for multiple robots based on Bayesian inference is proposed when multiple robots adopting multi-RAT (Radio Access Technology) communications exist in cognitive radio networks. Multiple robots are separately defined by primary and secondary users as in conventional mobile communications system. In addition, the heterogeneous spectrum environment is considered in this paper. To improve the performance of localization for multiple robots, a realistic multiple primary user distribution is explained by using the probabilistic graphical model, and then we introduce the Gibbs sampler strategy based on Bayesian inference. In addition, the secondary user selection minimizing the value of GDOP (Geometric Dilution of Precision) is also proposed in order to overcome the limitations of localization accuracy with Gibbs sampling. Via the simulation results, we can show that the proposed localization method based on GDOP enhances the accuracy of localization for multiple robots. Furthermore, it can also be verified from the simulation results that localization performance is significantly improved with increasing number of observation samples when the GDOP is considered.
Journal of Korean Academy of Fundamentals of Nursing
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v.15
no.3
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pp.321-331
/
2008
Purpose: Purpose of this study was to explore the process of menopause experiences in middle-aged women. Method: The grounded theory methodology by Strauss & Corbin was the basis for this study. The participants were 15 middle-aged women selected by theoretical sampling. The data were collected by in-depth interviews using audiotape recording analyzed simultaneously by the constant comparative method described in Strauss and Corbin's methodology. Results: Experiencerelated to menopause in middle-aged women is caused by cognition of the aging process, difficult problems in family that occur with limitation of social activity, and perception of changingseasons. The central incident of menopause in middle-aged women was loss of the woman's identity. Intervening conditions, which are action/interactional strategies for menopause, are related to social support. Action/interactional strategies related to menopause management included medical treatment, mind control, and participation in social activity. Experiencerelated to menopause in middle-aged women resulted in comfort or discomfot of physical and emotional condition. Conclusion: The findings of this study may contribute to the development health promotion strategy for middle-aged women. There is need to develop family support systems and preventive nursing interventions to avoid negative coping strategy.
Manual elections processes in Egypt have several negative effects; that mainly leads to political corruption due to the lack of transparency. These issues negatively influence citizen's participation in the political life; while electronic voting systems aim to increase efficiency, transparency, and reduce the cost comparing to the manual voting. The main research objectives are, finding the successful factors that positively affects E-voting implementation in Egypt, in addition of finding out the reasons that keep Egyptian government far from applying E-voting, and to come up with the road map that Egyptian government has to take into consideration to successfully implement E-voting systems. The findings of the study suggest that there are seven independent variables affecting e-voting implementation which are; leadership, government willingness, legal framework, technical quality, awareness, citizen's trust in government and IT literacy. Technology-Organization-Environment (TOE) theory was used to provide an analytical framework for the study. A quantitative approach (i.e., survey questionnaire) strategy was used to collect data. A random sampling method was used to select the participants for the survey, whom are targeted voters in Egypt and have access to the internet, since the questionnaire was distributed online and the data is analyzed using regression analysis. Practical implications of this study will lead for more citizen participation in the political life due to the transparency that E-voting system will create, in addition to reduce the political corruption.
The purpose of this study was to examine the sportswear purchase decision factors and brand preference of college students. The subjects in this study were 614 college students who were selected by cluster random sampling from Daegu and North Gyeongsang Province. The collected data were analyzed by crosstab analysis, and the findings of the study were as follows: If a sportswear company has college students as a target market, first, the company needs to consider design and utility. Second, the company needs to expand internet sale while maintaining a strategy for centering on speciality shop and department store as for a sale of sportswear. Third, the college students themselves have a right of choice according to purchasing sportswear. Thus, a distribution company requires a direct marketing strategy targeting college students. Fourth, simple design of adding a fashion trend is needed. Fifth, the sportswear company needs to expand production and sale in jumpers and trousers based on T-shirts. Sixth, color in sportswear needs to be composed of design based on gray or black color. In order for a sportswear company to be adjusted to the global market environment here after, it requires an effort to continuously grasp consumers' trend and to apply new design and color. Also, the company will be able to be equipped with competitive edge by producing diversely functional products that are demanded by the segmented market.
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