• Journal of the Korea Convergence Society
• /
• v.8 no.9
• /
• pp.285-292
• /
• 2017

This paper describes a recursive least-squares based convergent algorithm for driving characteristic classification for personalized autonomous driving. Recently, various researches on autonomous driving technology have been conducted for level 4 fully autonomous driving. In order for commercialization of the autonomous vehicle, personalized autonomous driving is required to minimize passenger's insecureness to the autonomous vehicle. To address this problem. this study proposes mathematical model that represents driving characteristics and recursive least-squares based algorithm that can estimate the defined characteristics. The actual data of two drivers has been used to derive driving characteristics and the hypothesis testing method has been used to classify two drivers. It is shown that the proposed algorithms can derive driving characteristics and classify two drivers reasonably.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.11
• /
• pp.66-78
• /
• 2015

With the development of bio computing technology, DNA watermarking to do as a medium of DNA information has been researched in the latest time. However, DNA information is very important in biologic function unlikely multimedia data. Therefore, the reversible DNA watermarking is required for the host DNA information to be perfectively recovered. This paper presents a reversible DNA watermarking using least square based prediction error expansion for noncodng DNA sequence. Our method has three features. The first thing is to encode the character string (A,T,C,G) of nucleotide bases in noncoding region to integer code values by grouping n nucleotide bases. The second thing is to expand the prediction error based on least square (LS) as much as the expandable bits. The last thing is to prevent the false start codon using the comparison searching of adjacent watermarked code values. Experimental results verified that our method has more high embedding capacity than conventional methods and mean prediction method and also makes the prevention of false start codon and the preservation of amino acids.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.33 no.10
• /
• pp.26-34
• /
• 2005

In this paper, a novel moving least squares interface welding method is proposed to carry out the coupled analysis of whole model composed of independently modeled finite element substructures with nodal mismatching interfaces. To verify the validity, and efficiency of the proposed interface welding method, various numerical examples are worked out including patch tests, convergence tests, and examples of coupled analyses of the structural systems with mismatching substructures. From the numerical tests, it is confirmed that one can efficiently carry out the coupled analysis of whole model composed of mismatching finite element substructures through the proposed method without any remeshing or any additional unknown.

• The Transactions of the Korea Information Processing Society
• /
• v.5 no.9
• /
• pp.2345-2352
• /
• 1998

The hyper-geometric distribution software reliability growth model was recently developed and successfully applied Due to mathematical difficultv of the maximum likclihmd method, the least squares method has hem suggested for parameter estimation by the previous studies. We first summarize and compare the minimization criteria adopted by the previous studies. It is theo shown that the weighted least squares method is more appropriate hecause of the nonhomogeneous variability of the number of newly detected faults. The adequacy of the weighted least squares method is illustrated by two numerical examples. Finally, we propose a new method fur predicting the number of faults newly discovered by next test instances. The new prediction method can be used for determining the time to stop testing.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.5
• /
• pp.931-940
• /
• 2011

Classification is to generate a rule of classifying objects into several categories based on the learning sample. Good classification model should classify new objects with low misclassification error. Many types of classification methods have been developed including logistic regression, discriminant analysis and tree. This paper presents a new classification method using penalized partial least squares. Penalized partial least squares can make the model more robust and remedy multicollinearity problem. This paper compares the proposed method with logistic regression and PCA based discriminant analysis by some real and artificial data. It is concluded that the new method has better power as compared with other methods.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.6 no.4
• /
• pp.43-52
• /
• 1986

With increasing of computer use, a least squares method is now widely used in the regression analysis of various data. Unreliable results of regression coefficients due to the floating point of computer and problems of ordinary least squares method are described in detail. To improve these problems, a least squares method using orthogonal function is developed. Also, Comparison and analysis are performed through an example of numerical test, and re-orthogonalization method is used to increase the accuracy. As an example of application, the optimum order of AR process for the time series of monthly flow at the Pyungchang station is determined using Akaike's FPE(Final Prediction Error) which decides optimum degree of AR process. The result shows the AR(2) process is optimum to the series at the station.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2024.01a
• /
• pp.419-422
• /
• 2024

본 논문에서는 다항식 보간법의 일종인 이동최소자승법(Moving least squares, MLS)을 네트워크로 학습하여, Divergence-constrained MLS 벡터장을 효율적으로 표현하는 방법을 제안한다. 벡터장을 구성하기 위해 MLS는 스칼라가 아닌 벡터 보간을 해야 하므로 행렬과 벡터의 크기가 더 커지며, 이는 계산량이 커짐을 나타낸다. 고차 보간(High-order interpolation)이 가능한 특징은 장점이 되지만, 계산량이 매우 크기 때문에 시뮬레이션에는 활용이 어렵다. Divergence-constrained MLS를 유체 시뮬레이션에 적용한 경우가 있지만, 실제로 슈퍼컴퓨터(Supercomputer)를 해야 장면 제작이 가능하므로 효용성이 떨어진다. 본 논문에서는 이러한 문제를 해결하기 위해 네트워크 학습을 통한 Divergence-constrained MLS 벡터장을 표현할 수 있는 결과를 보여준다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.12
• /
• pp.2353-2362
• /
• 2015

In this paper, we employ the single channel full duplex radio for wireless local area network (WLAN) systems, and design digital interference cancellers using adaptive signal processing. When the full duplex scheme is used for WLAN systems with multiple transmit and receive antennas, some interference is caused through the feedback of transmit signals from multiple antennas. To remove the feedback interference, we derive the least mean square (LMS), normalized LMS (NLMS), and recursive least squares (RLS) algorithms based on adaptive signal processing techniques. In addition, we analyze the theoretical convergence of the proposed LMS and RLS methods. The channel capacity of full duplex radios increases by two times than that of half duplex radios, when the packet error rate (PER) performances for the two systems are identical. Through numerical simulations in WLAN systems, it is shown that the full duplex method with the proposed interference cancellers has a similar PER performance with the conventional half duplex transmission scheme.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.25 no.2
• /
• pp.175-182
• /
• 2012

In this paper we are concerned with the performance of structural stability of torsion in square cross section of a beam with holes. The critical load is defined as the smallest load at which the equilibrium of the structure fails to be stable as the load is slowly increased from zero. The beams subjected to torsion are frequently encountered in general structures and these forces influence to the stability of structure. The boundary element method is found to be very efficient and accurate for the analysis of torsion problems including complex boundary conditions with respect to its simplicity and generality. In this paper, it is required to derive the boundary element formulation for torsion problem and integrate directly on the discrete boundary. To investigate the validity of the developed computer program, three distinctly solid cross-sections which are elliptical, rectangular and triangular one are analyzed, and comparisons are made with analytical approaches where these can also be used.

• Journal of the Korea Computer Graphics Society
• /
• v.23 no.4
• /
• pp.1-9
• /
• 2017

We propose an efficient method to determine the position of blueprint by using a vector field with optimized MLS(Moving Least Squares). Typically, a professional architectural design office takes a long time to work as well as a high processing cost because the designer manually determines the location to place the buildings in a specific area. In order to solve this inefficient problem, we propose a method to automatically determine the location of the blueprint based on the optimized MLS method. In the proposed framework, the designer selects the desired region in the actual city data and calculates the flow of the vector based on the region. Use the optimized MLS method to extract the vector field and determine the amount of rotation of the drawing based on this field. The location of the blueprint determined by the proposed method is very similar to the flow seen when the actual building is located. As a result, the efficiency of the overall architectural design process is further improved by reducing the designer's inefficient workforce.