• Structural Engineering and Mechanics
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• v.47 no.3
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• pp.307-329
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• 2013

The bending problem of Euler-Bernoulli discontinuous beams is dealt with, in which the discontinuities are due to the loads and eventually to essential constrains applied along the beam axis. In particular, the loads are modelled as random delta-correlated processes acting along the beam axis, while the ulterior eventual discontinuities are produced by the presence of external rollers applied along the beam axis. This kind of structural model can be considered in the static study of bridge beams. In the present work the exact expression of the response quantities are given in terms of means and variances, thanks to the use of the stochastic analysis rules and to the use of the generalized functions. The knowledge of the means and the variances of the internal forces implies the possibility of applying the reliability ${\beta}$-method for verifying the beam.

• Communications of Mathematical Education
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• v.21 no.4
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• pp.597-612
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• 2007

For finding the optimal strategy in Blackout game which was introduced in the homepage of popular movie "Beautiful mind", we have developed and generalized a mathematical proof and an algorithm with a couple of softwares. It did require only the concept of basis and knowledge of basic linear algebra. Mathematical modeling and analysis were given for the square matrix case in(Lee,2004) and we now generalize it to a generalized $m{\times}n$ Blackout game. New proof and algorithm will be given with a visualization.

• Journal of Elementary Mathematics Education in Korea
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• v.15 no.1
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• pp.39-56
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• 2011

In 7th grade textbooks, the distributive property is generalized as in algebraic forms, and it seems that the students have not so good grip on this property. To get a good stock of knowledge on that generalized property, full understanding of it in concrete context should take precedence. This study would aim to propose some educational implications for better understanding of that property, through analysing the contents of it comparatively in Korean and Japanese elementary textbooks.

• Journal of Korean Association for Spatial Structures
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• v.3 no.2 s.8
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• pp.101-107
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• 2003

There exists a structural problem for link structures in the unstable state. The primary characteristics of this problem are in the existence of rigid body displacements without strain, and in the possibility of the introduction of prestressing to change an unstable state into a stable state. When we make local linearized incremental equations in order to obtain knowledge about these unstable structures, the determinant of the coefficient matrices is zero, so that we face a numerically unstable situation. This is similar to the situation in the stability problem. To avoid such a difficult situation, in this paper a simple and straightforward method was presented by means of the generalized inverse for the numerical analysis of stability problem.

• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.482-489
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• 2006

This paper presents the generalized dynamic modeling of self-excited induction generator (SEIG) using state-space approach. The proposed dynamic model consists of induction generator; self-excitation capacitance and load model are expressed in stationary d-q reference frame with the actual saturation curve of the machine. An artificial neural network model is implemented to estimate the machine magnetizing inductance based on the knowledge of magnetizing current. The dynamic performance of SEIG is investigated under no load, with the load, perturbation of load, short circuit at stator terminals, and variation of prime mover speed, variation of capacitance value by considering the effect of main and cross-flux saturation. During voltage buildup the variation in magnetizing inductance is taken into consideration. The performance of SEIG system under various conditions as mentioned above is simulated using MATLAB/SIMULINK and the simulation results demonstrates the feasibility of the proposed system.

• Journal of KIEE
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• v.10 no.1
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• pp.7-15
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• 2000

Source separation is a statistical method, the goal of which is to separate the linear instantaneous mixtures of statistically independent sources without resorting to any prior knowledge. This paper addresses a source separation algorithm which is able to separate the mixtures of sub- and super-Gaussian sources. The nonlinear function in the proposed algorithm is derived from the generalized Gaussian distribution that is a set of distributions parameterized by a real positive number (Gaussian exponent). Based on the relationship between the kurtosis and the Gaussian exponent, we present a simple and efficient way of selecting proper nonlinear functions for source separation. Useful behavior of the proposed method is demonstrated by computer simulations.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.139-147
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• 1996

PID control has been widely used for real control systems. Particularly, there are many researches on control schemes of tuning PID gains. However, to the best of our knowledge, there is no result for discrete-time systems with unknown time-delay and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown papameters and unknown time-delay system. A numerical simulation was presented to illustrate the effectiveness of this method.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5493-5498
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• 2015

Due to the lack of nationwide population-based cancer registration, the total cancer prevalence in Iran is unknown. Our previous work in which we used a basic network scale-up (NSU) method, failed to provide plausible estimates of total cancer prevalence in Kerman. The aim of the present study was to estimate total and partial prevalence of cancer in southeastern Iran using an adapted version of the generalized network scale-up method. A survey was conducted in 2014 using multi-stage cluster sampling. A total of 1995 face-to-face gender-matched interviews were performed based on an adapted version of the NSU questionnaire. Interviewees were asked about their family cancer history. Total and partial prevalence were estimated using a generalized NSU estimator. The Monte Carlo method was adopted for the estimation of upper/lower bounds of the uncertainty range of point estimates. One-yr, 2-3 yr, and 4-5 yr prevalence (per 100,000 people) was respectively estimated at 78 (95%CI, 66, 90), 128 (95%CI, 118, 147), and 59 (95%CI, 49, 70) for women, and 48 (95%CI, 38, 58), 78 (95%CI, 66, 91), and 42 (95%CI, 32, 52) for men. The 5-yr prevalence of all cancers was estimated at 0.18 percent for men, and 0.27 percent for women. This study showed that the generalized familial network scale-up method is capable of estimating cancer prevalence, with acceptable precision.

• Journal of Korean Biological Nursing Science
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• v.22 no.4
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• pp.260-270
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• 2020

Purposes: Sepsis is a critical condition in which nurses should detect clinical manifestations and provide early intervention to prevent unwanted serious conditions in the patients. The initial occurrence and management of sepsis take place in general units, but there is a lack of knowledge in nurses. The purpose of this study was to examine the effects of a case-based sepsis education program and compare the case-based education program with and without smartphone applications. Methods: A quasi-experimental pre-test-post-test design with a control group was used. We provided a case-based education program with and without smartphone applications to the nurses and tested the effects of the program on knowledge, the accuracy of sepsis assessment, and self-efficacy as outcome variables. A total of 60 nurses in general units participated. To test differences in knowledge, the accuracy of sepsis assessment, and self-efficacy regarding sepsis between the groups over time, a mixed-design ANCOVA was used for parametric analysis, and generalized estimating equations (GEE) were used for nonparametric analysis. Results: There were significant differences in knowledge, the accuracy of sepsis assessment, and self-efficacy between the groups and within the groups over time. The intervention groups treated with the case-based education program showed improved outcome variables compared to the control group. There was no difference between case-based education with the smartphone application or without the application. Conclusions: The case-based education improved knowledge, the accuracy of sepsis assessment, and self-efficacy in the care of sepsis by nurses working in the general wards. The results suggest that the case-based education program for nurses was effective and eventually improved patient health outcomes.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.408-411
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• 1993

In this paper, we propose the Fuzzy Neural Controller with a Self-Organizing Map based on the fuzzy relation neuron. The fuzzy ndes expressing the input-output relation of the system are obtained by using the fuzzy relation neuron and updated automatically by means of the generalized delta rule. Also, the proposed method has a capability to express the knowledge acquired from the input-output data in form of fuzzy inferences rules. The learning algorithm of this fuzzy relation neuron is described. The effectiveness of the proposed fuzzy neural controller is illustrated by applying it to a number of test data sets.