• Journal of the Optical Society of Korea
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• v.20 no.3
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• pp.341-357
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• 2016

A novel asymmetric multiple-image encryption method using an octonion Fresnel transform (OFST) and a two-dimensional Sine Logistic modulation map (2D-SLMM) is presented. First, a new multiple-image information processing tool termed the octonion Fresneltransform is proposed, and then an efficient method to calculate the OFST of an octonion matrix is developed. Subsequently this tool is applied to process multiple plaintext images, which are represented by octonion algebra, holistically in a vector manner. The complex amplitude, formed from the components of the OFST-transformed original images and modulated by a random phase mask (RPM), is used to derive the ciphertext image by employing an amplitude- and phase-truncation approach in the Fresnel domain. To avoid sending whole RPMs to the receiver side for decryption, a random phase mask generation method based on SLMM, in which only the initial parameters of the chaotic function are needed to generate the RPMs, is designed. To enhance security, the ciphertext and two decryption keys produced in the encryption procedure are permuted by the proposed SLMM-based scrambling method. Numerical simulations have been carried out to demonstrate the proposed scheme's validity, high security, and high resistance to various attacks.

• The Korean Journal of Health Service Management
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• v.13 no.1
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• pp.67-78
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• 2019

Objectives: To identify the factors affecting the cognitive function according to the education level of people aged 65 or older. Methods: This study used the data from the 2014 survey of living conditions and welfare needs of Korean older adults. A total of 10,248 people were analyzed in the final analysis, not including those who responded by proxy and those who did not participate in cognitive function tests. Cognitive function was measured by Mini Mental State Examination -Dementia Screening(MMSE-DS), and logistic regression was performed using the SPSS/WIN 24.0 program. Results: There were differences in factors affecting cognitive function depending on the education level. Overall, regular exercise had a positive effect on maintaining cognitive function, and the higher the education level, the more important it was to maintain the Instrumental Activities of Daily Living(IADL). In addition, for lower education levels, improving the life satisfaction was important to prevent the decline of cognitive function. Conclusions: Based on the results of this research, it is suggested that customized approaches shoud be taken according to education level when developing and implementing programs to prevent the decline of cognitive function.

• Journal of Advanced Navigation Technology
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• v.17 no.3
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• pp.292-297
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• 2013

In this paper, The design of digital circuits for chaotic composition function which is used for the key-stream generator is studied in this work. The overall design concept and procedure due to the mathematical model of chaotic key-stream generator is to be the explained in detail, and also the discretized truth table of chaotic composition function is presented in this paper. consequently, a composition state machine based on the compositive map with connecting two types of one dimensional and two dimensional chaotic maps together is designed and presented.

• The Korean Journal of Health Service Management
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• v.10 no.3
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• pp.147-158
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• 2016

Objectives : The aim of this study was to investigate predictors of cognitive function decline among community dwelling elderly. Methods : Data were analyzed from the Survey of Living Condition of Elderly panel study. Cognitive function was measured with the MMSE-KC at baseline and year 3. The study subjects were 5,464 community dwelling people aged 65 years or older who had no disability at baseline. Logistic regression analysis was used to predict cognitive function decline. Results : From 2008-2011, 4,417(80.8%) elderly people had no cognitive decline, and 1,074(19.2%) showed cognitive function decline measured by the MMSE-KC. After adjusting for demographics and baseline MMSE-KC score, the best predictors for cognitive function decline at 36 months were diabetes mellitus, smoking, low intensity physical activity, relationship with relatives and friends. Conclusions : Health promotion programs that are focused on the elderly are essential in preventing cognitive function decline. Promoting regular physical activity, and social relationships should be included in health promotion for elderly. When treating patients with diabetes, preventing cognitive impairment should be considered through education and counseling.

• Journal of the military operations research society of Korea
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• v.6 no.2
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• pp.129-149
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• 1980

In medical follow-up, equipment lifetesting, various military situations, and other fields, one often desires to calculate survival probability as a function of time, p(t). If the observer is able to record the time of occurrence of the event of interest (called a 'death'), then an empirical, non-parametric estimate may simply by obtained from the fraction of survivors after various elapsed times. The estimation is more complicated when the data are truncated, i.e., when the observer loses track of some individuals before death occurs. The product-limit method of Kaplan and Meier is one way of estimating p(t) when the mechanism causing truncation is independent of the mechanism causing death. This paper proposes jackknife estimators of logistic trans-formation and compares it to the product-limit method. A computer simulation is used to generate the times of death and truncation from a variety of assumed distributions.

• Journal of Environmental Policy
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• v.2 no.1
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• pp.77-86
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• 2003

Particle-size distributions (PSDs) are widely used for the estimation of soil hydraulic properties. The objective of this study was to select the best model among the nine PSD models with different underlying assumptions, by using a variety of Korean soils. The Fredlund model with four parameters, the logistic growth curve, and Weibull distribution model showed the highest performance compared to the other models with the majority of soils studied. It was interesting to find that the logistic growth function with no fitting parameters showed a great fitting performance.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.310-324
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• 2015

The stream cipher Salsa20 and its reduced versions are among the fastest stream ciphers available today. However, Salsa20/7 is broken and Salsa20/12 is not as safe as before. Therefore, Salsa20 must completely perform all of the four rounds of encryption to achieve a good diffusion in order to resist the known attacks. In this paper, a new variant of Salsa20 that uses the chaos theory and that can achieve diffusion faster than the original Salsa20 is presented. The method has been tested and benchmarked with the original Salsa20 with a series of tests. Most of the tests show that the proposed chaotic Salsa of two rounds is faster than the original four rounds of Salsa20/4, but it offers the same diffusion level.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.421-431
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• 2014

The market basket data in the form of a binary user-item matrix or a binary item-user matrix can be modelled as a binary classification problem. The binary logistic regression approach tackles the binary classification problem, where principal components are predictor variables. If users or items are sparse in the training data, the binary classification problem can be considered as a cold-start problem. The binary logistic regression approach may not function appropriately if the principal components are inefficient for the cold-start problem. Assuming that the market basket data can also be considered as a special regression problem whose response is either 0 or 1, we propose three supervised learning approaches: random forest regression, random forest classification, and elastic net to tackle the cold-start problem, comparing the performance in a variety of experimental settings. The experimental results show that the proposed supervised learning approaches outperform the conventional approaches.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.525-526
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• 2016

machine learning 기법 중 하나인 logistic regression을 이용하여 benign sample과 breast cancer sample을 구분할 수 있는데, 이 연구를 통해 classification의 정확도를 높이고 false positive와 false negative의 비율을 줄이려고 했다. 그래서 logistic regression의 parameter 값을 바탕으로 regression function에 영향을 많이 주는 feature 들을 선택하고, 영향력 있는 feature 들을 더한 새로운 feature를 추가했다. 그 결과 정확도와 F-score가 증가했으며, false positive, false negative의 비율이 감소했다.

• Journal of the Korea Safety Management & Science
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• v.3 no.1
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• pp.35-44
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• 2001

Today's environment of enterprise is changing. They have to face customers' demands with the right product, the right service and supply them at the right time. And aIso cut down logistics and inventory cost and bring up the Profit as much as they can. This means the change of putting enterprise first in importance to putting customer first in importance. therefore to correspond to customer's demand, shorting lead time is becoming a essential condition. The answer to this changes of environment is supply chain management In this study, we use Goldratt's drum-buffer-rope scheduling in between manufacturer and supplier. And when shortage of inventory occur, search for the supply chain's CCR. Pressing CCR for more production, and supply Inventory from logistic center to guide for inventory buffing. using logistic warehouse between manufacturer and supplier, can execute function of buffer.