• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.10a
• /
• pp.301-304
• /
• 2015

센서네트워크는 기본적으로 센서 데이터를 활용하고 있기 때문에 센서 데이터는 센서네트워크의 구성요소 중 가장 중요하다 해도 과언이 아니다. 하지만 통신장애 발생 시 다양한 특징을 갖는 센서 데이터의 손실이 발생할 수 있다. 본 논문에서는 이를 위해 최대/최소값 중심으로 센서 데이터를 메모리에 저장 및 압축하는 2MC 방법을 제안하고, 보간법을 사용하여 데이터 복구 후 실제 데이터와 비교하여 그 성능을 검증하였다. 실험결과, 기존 방법과 비교하여 최대 8배까지 압축한 복구 데이터를 실제로 사용할 수 있는 정도이며, 평균 오차율은 8배 압축에서 기존 압축 방법 대비 최대 35% 감소하였다.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2003.04a
• /
• pp.221-224
• /
• 2003

이 연구는 국내의 균열암반에 대한 지하수 유동 연구가 대수층이 등방이라는 가정하에 진행피고 있는 방법에서 벗어나 대수층이 이방성을 띤다는 가정하에 대수층의 수리적 이방성을 해석하는데 중점을 두었다. 수리시험은 30.91 $m^3$/day로 BH-1공에서 300분간 양수였으며, 각각의 관측공 BH-2, BH-3, BH-4, 및 BH-5공에서 시간에 따른 수위강하를 관측하였다. 수리시험에 의해 얻어진 시간별 수위강하 자료를 이용하여 Jacob(1950)의 직선법에 의해서 직선의 기울기(m)와 수위강하가 영이 되는 지점에서의 시간( $t_{0}$)을 계산하였다. 대수층의 수리학적 이방성 텐서 (tensor) 즉, 최대투수량계수텐서 ( $T_{ξξ}$)와 최소투수량계수텐서 ( $T_{ηη}$)를 산출하기 위해서 Stewart(1973)에 의해서 정립된 정규최소제곱(Ordinary least-square)방법을 적용하였으며, 이 방법은 관측공이 최소한 4개를 필요로 한다. 그 결과로, $T_{ξξ}$는 12.21 $m^2$/day이고 $T_{ηη}$는 10.47 $m^2$/day로 산출되었다. 최대투수량계수텐서의 방향은 Nl9.13$^{\circ}$E 이고 이방성율은 1.17로 산출되었다. BH-1공에서 수리시험시 대수층의 이방성은 등방성에 가깝게 표현되었다. 이는 연구지역 대수층이 다수의 균열에 의해서 수리적 상호연결성이 고루 분포된 것으로 판단된다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.16 no.5
• /
• pp.61-65
• /
• 2002

RM(Switched Reluctance Motor)＇s Torque is generated by phase-current and inductance profile. A new analytical concept is proposed to determine the turn-off angle for maximization of the torque output. This paper describes a new method to maximization the average torque of a current control Switched Reluctance Motor. It is based on the simplified turn-off angle equation using least square method. Simulations carried out on a three-phase 6/4 pole SRM justify the algorithm is described. The suggested maximization average torque is verified by simulation in this paper.

• Korean Journal of Optics and Photonics
• /
• v.4 no.4
• /
• pp.363-372
• /
• 1993

An optimization technique with variable orthogonalization and SVD(singular value decomposition) is examined in a double-Gauss type photographic lens design and its convergence and stability are compared with ordinary least squares and DLS(damped least squares) method. It is known that there are close relationship between the stability of optimization and condition number of nomal equation, the ratio between maximum and minimum of eigenvalues. In this study, the stability is greatly improved by limiting the condition number, the SVD, as expeded. The case of DLS with small damping, orthogonalization and SVD shows the most rapid convergence and stability. It means that the unstability of DLS method with small damping is overcome by using the variable orthogonalization and SVD.

• The KIPS Transactions:PartB
• /
• v.13B no.4 s.107
• /
• pp.393-400
• /
• 2006

There are many feature extraction methods for face recognition. We need a new method to overcome the small sample problem that the number of feature variables is larger than the sample size for face image data. The paper considers partial least squares(PLS) as a new dimension reduction technique for feature vector. Principal Component Analysis(PCA), a conventional dimension reduction method, selects the components with maximum variability, irrespective of the class information. So, PCA does not necessarily extract features that are important for the discrimination of classes. PLS, on the other hand, constructs the components so that the correlation between the class variable and themselves is maximized. Therefore PLS components are more predictive than PCA components in classification. The experimental results on Manchester and ORL databases shows that PLS is to be preferred over PCA when classification is the goal and dimension reduction is needed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.23 no.9
• /
• pp.62-66
• /
• 2009

Three inputs of given three magnetic fluxes of an induction motor are calculated. Then, the calculation of magnetic flux for minimum input is repeated using quadratic interpolation method until the convergence criteria are satisfied. The maximum efficiency control is fulfilled with the final magnetic flux for minimum input. Simulation results verify the effectiveness of the proposed method.

• Korean Journal of Optics and Photonics
• /
• v.19 no.3
• /
• pp.182-186
• /
• 2008

The prism spectrometer is a standard device for the measurement of refractive index; it is used in undergraduate laboratories. Typically, however, lots of attention is required in the alignment, and the accuracy of the obtained refractive index is not so high in spite of the durability of the device. The maximum and minimum deviation method, which compensates the disadvantages of the prism spectrometer, can be composed cost effectively using a length marking tape and a rotating platform. It can measure the refractive indices accurately by utilizing a wide screen. In this study, the equal sided hollow prism whose length is 26 mm was fabricated and measured the refractive indices of seven kind of liquids (pure water, $C_3H_5(OH)_2$, $CCl_4$, $C_6H_4NH_2$, $CS_2$, $C_6H_4(CH_3)_2)$ by using the prism spectrometer and maximum and minimum deviated laser beam method at the wavelengths of He-Ne laser (${\lambda}$= 632.8 nm) and YVO4 laser (${\lambda}$= 532 nm). The result shows that the data obtained by the latter method are more accurate and precise than those obtained by the former device.

• Environmental and Resource Economics Review
• /
• v.13 no.2
• /
• pp.245-269
• /
• 2004

While the role of local community is getting important in reducing greenhouse gases, current financial supports have not considered these efforts. Instead, development activities have been the only basis of fiscal distribution, which have led to unsustainable development. In this context, this paper analyzes the emission and absorb of air pollutants by local districts in Daegu Metropolitan city and constructs an empirical energy database for local energy use and environmental emissions. Based on the data, it prioritized environmental contribution by region through using MCDM methods, that include maximin & maximax method, simple additive weighting (SAW) and hierarchical additive weighting method (HAW). This concludes the possibility of policy methodology through which we can input environmental variables in distributing local budget.

• Journal of Korean Society of Forest Science
• /
• v.85 no.2
• /
• pp.149-157
• /
• 1996

The applications of multiple criteria decision making(MCDM) methods were investigated to determine the priority order in forest road construction for timber harvesting and silvicultrual activities in 22 regions. In this paper, MCDM methods have five methods from two kinds of models. The one is non-compensatory preference model including maximin and maximax method; the other is compensatory preference model including simple additive weighting method(SAW), hierarchical additive weighting method(HAW) and technique for order preference by similarity to ideal solution(TOPSIS), SAW and TOPSIS methods turned out to be the most adequate for forest road construction priority order among the five methods tested in this study.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.5
• /
• pp.1153-1165
• /
• 2017

Structural equation modeling (SEM) is a basic tool for testing theories in a variety of disciplines. A maximum likelihood (ML) method for parameter estimation is by far the most widely used in SEM. Alternatively, two-stage least squares (2SLS) estimator has been proposed as a more robust procedure to address model misspecification. A regularized extension of 2SLS, two-stage ridge least squares (2SRLS) has recently been introduced as an alternative to ML to effectively handle the small-sample-size issue. However, it is unclear whether and when misspecification and small sample sizes may pose problems in theory testing with 2SLS, 2SRLS, and ML. The purpose of this article is to evaluate the three estimation methods in terms of inferences errors as well as parameter recovery under two experimental conditions. We find that: 1) when the model is misspecified, 2SRLS tends to recover parameters better than the other two estimation methods; 2) Regardless of specification errors, 2SRLS produces small or relatively acceptable Type II error rates for the small sample sizes.