• Journal of Forest and Environmental Science
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• v.28 no.4
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• pp.205-211
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• 2012

Yield tables are a frequently used data base for regional timber resource forecasting. A normal yield table is based on two independent variables, age and site (species constant), and applies to fully stocked (or normal) stands while empirical yield tables are based on average rather than fully stocked stands. Normal and empirical yield tables essentially have many limitations. The limitations of normal and empirical yield tables led to the development of variable density yield tables. Mathematical models for estimating timber yields are usually developed by fitting a suitable equation to observed data. The model is then used to predict yields for conditions resembling those of the original data set. It may be accurate for the specific conditions, but of unproven accuracy or even entirely useless in other circumstances. Thus, these models tend to be specific rather than general and require validation before applying to other areas. Dalbergia sissoo forms a major portion of irrigated plantations in the hot desert of India and is an important timber tree species where stem wood is primarily used as timber. Variable density yield model is not available for this species which is very crucial in long-term planning for managing the plantations on a sustained basis. Thus, the objective of this study was to develop variable density yield model based on the data collected from 30 sample plots of D. sissoo laid out in IGNP area of Rajasthan State (India) and measured annually for 5 years. The best approximating model was selected based on the fit statistics among the models tested in the study. The model develop was evaluated based on quantitative and qualitative statistical criteria which showed that the model is statistically sound in prediction. The model can be safely applied on D. sissooo plantations in the study area or areas having similar conditions.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.591-596
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• 2022

Since 4-bar linkage widely used in various industrial fields has a fixed link length, it is inconvenient to add an independent link structure or control device to change the movement of output link. Therefore, this paper proposes a new concept of variable 4-bar linkage mechanism to selectively adjust the movement of the output link to fit desired situations, and applied to the commercial table fans, which is a representative product using a 4-bar linkage system. The optimal rotation angle steps for efficiency are determined experimentally and the appropriate lengths of linkage to fit each step are calculated analytically. Changes in the linkage length are implemented by the rotational motion using a grooved cylindrical cam and the feasibility of the proposed variable linkage mechanism is verified through fabrication and measurement. The presented variable link mechanism is expected to improve the efficiency of industrial robots and fuel valve systems.

• Journal of the Korean Statistical Society
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• v.17 no.2
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• pp.81-92
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• 1988

We observe independent random variable $Y_i \sim N(\theta_i,1), i=1,2,\cdots,k$, and we are interested in detecting the treatment with the largest $\theta_i$. We consider a procedure which infers $\theta_{(k)} \geq max\theta_i (i\neq(k))$ whenever $Y_{(k)} \geq maxY_i+C (i\neq(k))$. The maximum probability of a false inference is found, and it is shown that the inference can be made with the two-sample one-sided critical value for the usual error levels. The result also holds in the case of common unknown variance.

• Kyungpook Mathematical Journal
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• v.48 no.3
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• pp.411-417
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• 2008

In the present paper we derive the distribution of single order statistics, joint distribution of two order statistics and the distribution of product and quotient of two order statistics when the independent random variables are from continuous Kumaraswamy distribution. In particular the distribution of product and quotient of extreme order statistics and consecutive order statistics have also been obtained. The method used is based on Mellin transform and its inverse.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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• 1996.10a
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• pp.50-54
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• 1996

극치확률 모델과 더불어 최극해면분석에 이용되는 또 하나의 방법은 조석 및 비조석성분의 복합확률방법(joint probability method)으로 Pugh와 Vassie(1978)에 의해 제시되었다. 이 방법은 조석(tide)과 비조석성분(surge)이 통계적으로 독립적인 변수(statistically independent variable)로 취득될 수 있는 가를 일차적으로 분석한 후 해면의 확률분포를 조위분석함수(tidal probability distribution function)와 비조석성분분포함수(surge probability distribution function)의 복합으로서 산정하는 것이다. (중략)

• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.126-135
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• 2003

A basic assumption in standard applications of control charts is that the observations are statistically independent. However, this assumption is often violated from processes in many industries. The presence of autocorrelation has a serious impact on the performance of control charts, causing a dramatic increase in the frequency of false alarms. This paper considers a process in which the observations can be modeled as a first order autoregressive(AR(1)) process, and develops (equation omitted) charts with the variable sample size(VSS) scheme for monitoring the mean of this process.

• Bulletin of the Korean Mathematical Society
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• v.33 no.3
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• pp.377-383
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• 1996

We consider in this paper the following nonlinear regression model $$ (1.1) y_t = f(x_t, \theta_o) + \in_t, t = 1, \ldots, n, $$ where $y_t$ is the tth response, $x_t$ is m-vector imput variable, $\theta_o$ is a p-vector of unknown parameter belong to a parameter space $\Theta, f:R^m \times \Theta \ to R^1$ is a nonlinear known function, and $\in_t$ are independent unobservable random errors with finite second moment.

• Communications for Statistical Applications and Methods
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• v.11 no.2
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• pp.255-264
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• 2004

Due to a computerized data processing, there are many cases when we encounter a huge data set. On the other hand, advances in computing technologies make it possible to deal with a huge data set. One important area is the data mining. In this paper we consider data mining when the dependent variable is binary. The proposed method is to use the poly-class model when the independent variables consists of continuous and discrete variables. An example is provided.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.8
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• pp.1211-1220
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• 1990

This paper describes and implements a design method of register allocation as a required module of RISC compiler systems. It compiles a C program to a machine-independent intermediate language, translates each variable into symbolic register. After local allocation process for the symbolic registers, global register allocation is executed by applying the graph coloring algorithm. This register allocation phase is designed for a system with the large register file like RISC machines.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.543-552
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• 2007

We consider estimation of the right-tail probability in a half-triangle distribution, and also consider inference on reliability, and derive the k-th moment of ratio of two independent half-triangle distributions with different supports. As we define a skew-symmetric random variable from a symmetric triangle distribution about origin, we derive its k-th moment.