Earticle

본 논문에서는 로봇의 전역경로계획을 위한 지원맵 생성방법 중 적의 위협도를 고려한 위협맵 작성 방법에 대해 연 구하였다. 한국군 군대부호에 명시되는 정보 중 로봇 경로계획에 대한 정보들을 분류하고, 이에 대해 각 무장에 대 해 가정된 가중치를 부여하여 위협맵을 작성할 수 있도록 하였다. 위협 정도에 대한 자료구조 및 데이터를 분석하고 아군 로봇과 비교하여 위협도를 산출하였다. 또한 적의 위협 정도를 수식적으로 함수화하였으며 최소자승법을 통해 정량적으로 수치화하였다. 이렇게 산출된 위협도를 작전지역에 가시화하여 위협맵을 생성하였으며, 위협도를 반영 한 로봇의 경로를 계획하도록 하였다. 최종적으로 제시한 알고리즘에 대하여 시나리오 및 실험결과를 통해 성능을 검증하였다.

This paper proposes a threat map generation method considering the threat of enemy for robot path planning. Through classifying information for robot path planning of ROK military code and assuming a weight for each weapon, the threat level can be created. The threat level could be yielded by analyzing the data structure of threat and compared to our robots. Also, enemy's threat is formulated quantitatively using least square method and, the threat map is created visible in the area of operations for robot. Finally, the presented algorithm is verified performance through experimental results with scenarios.

국가정책 및 사회적 여건의 변화에 따라 도시부의 교통혼잡 완화를 위한 물리적 도로 확대가 한계에 다다른 지금 혼잡 완화를 위해서는 기존 도로의 효율성을 재고하는 방안이 간구되어야한다. 또한 지능형교통체계(ITS)는 과거 루프 및 영상검지기 등을 통한 도로기반 지점검지 중심의 교통정보 수집체계에서 도로, 자동차 및 보행자간의 다양한 수집 체계를 통한 실시간 구간검지 체계 중심의 차세대 지능형교통체계(C-ITS :Co-operative ITS)로 빠르게 진화하고 있으나 현재 교차로의 운영 및 제어를 위한 교통정보의 수집방법은 지점검지체계에 국한되어 있는 실정이다. 따라서 본 연구는 현재 Hi-pass에 적용된 DSRC기술을 통해 수집이 가능한 구간정보를 이용하여 접근로의 대기행렬 길이를 산정하고 이를 활용하는 독립교차로의 실시간 신호제어모형의 개발 및 평가를 목적으로 하였다. 대기행렬길이 추정을 위해 구간검지기를 통해 수집된 개별차량의 통행시간을 이용하여 시공도 상에 4개의 좌표값을 추정하였으며 한 주기동안 추정된 좌표값들을 통해 대기행렬이 생성되는 충격파의 속도 및 대기행렬길이를 추정하였다. 실시간 신호제어를 위해 각 방향별 추정된 대기행렬길이를 통해 전체 교차로의 대기행렬길이의 합이 최소가 되는 신호시간을 산정하였으며 API 기능을 제공하는 미시적 시뮬레이션 프로그램인 VISSIM을 활용하여 총 3개의 시나리오를 평가하여 알고리즘에 의해 교차로의 대기행렬길이의 합이 최소가 되는 신호시간의 산정이 가능함을 확인하였다.

The expansion of the physical road in response to changes in social conditions and policy of the country has reached the limit. In order to alleviate congestion on the existing road to reconsider the effectiveness of this method should be asking. Currently, how to collect traffic information for management of the intersection is limited to point detection systems. Intelligent Transport Systems (ITS) was the traffic information collection system of point detection method such as through video and loop detector in the past. However, intelligent transportation systems of the next generation(C-ITS) has evolved rapidly in real time interval detection system of collecting various systems between the pedestrian, road, and car. Therefore, this study is designed to evaluate the development of an algorithm for queue length based real-time traffic signal control methodology. Four coordinates estimate on time-space diagram using the travel time each individual vehicle collected via the interval detector. Using the coordinate value estimated during the cycle for estimating the velocity of the shock wave the queue is created. Using the queue length is estimated, and determine the signal timing the total queue length is minimized at intersection. Therefore, in this study, it was confirmed that the calculation of the signal timing of the intersection queue is minimized.

This paper deals with the construction of system for correct location determination of fixed tag. We adapted to construct the above method. Also we adapted the several filtering method. This system was constructed through using of several filtering methods to decrease the location determination error and fingerprint method which is composed of training phase and positioning phase. We constructed this system using Labview 2010 and MS-SQL 2000 as database. This system results in less location determination error than least square method, triangulation positioning method, and other fingerprint methods.

본 연구는 한국청소년패널조사 1차 자료를 분석하여 청소년의 비행행동과 공격성간의 쌍방적 관계를 검증하기 위함이다. 즉, 기존의 연구에서 검증된 바 있는 공격성이 비행행동의 예측요인이라는 사실에 더해서 그 반대적인 관계 역시 실증적으로 검증될 수 있음을 밝힌다. 이를 위해 청소년 비행행동 방정식과 공격성 방정식을 하나의 연립방정식 체계로 구성하여 2단계 최소제곱법(two Stage Least-Squares Method: 2SLS)으로 분석하였다. 분석결과 비행행동과 공격성은 서로 쌍방적인 관계를 갖는 것으로 분석되었다. 즉, 공격성이 비행행동을 유발하는 원인이 되기도 하지만 일련의 비행행동을 통한 경험자체 역시 청소년의 공격 성을 증가시키는 요인으로 작용하는 것이다. 이러한 연구는 청소년의 비행행동과 공격성에 대한 기존의 일면적(unilateral relationship)인 분석이 갖는 제한점을 극복하고 쌍방적 관계의 가능성을 제시하고자 한다. 이를 통해 청소년의 비행행동과 공격성과의 관계에 대한 이론적 논의를 더욱 풍부하게 할 수 있는 토대를 마련할 수 있을 것으로 기대한다.

The purpose of this study is to verify the inter-relationship between the delinquent behavior of the adolescents and aggressiveness. To fulfill this purpose, this study used the first data of the National Youth Policy Institute(NYPI) which was collected from middle school students(male: 1,725, female: 1,724). To analyze the inter-relationship between the adolescents' delinquent behavior and aggressiveness, 2SLS(Two Stage Least Square method) assumption method of simultaneous equations was used. By applying this simultaneous equation model, this study found, in addition to the previously verified fact that aggressiveness is the predicting factor for adolescents' delinquent behavior, that the opposite relationship also can be practically verified. That is, aggressiveness and delinquent behavior is not in an unilateral relationship that aggressiveness that aggressiveness has effect on delinquent behavior but is in a bilateral relationship that some part of delinquent behavior increases aggressiveness.

Solar photovoltaic (PV) system shows a non-linear current (I) –voltage (V) characteristics, which depends on the surrounding environment factors, such as irradiance, temperature, and the wind. Solar PV system, with current (I) - voltage (V) and power (P) - Voltage (V) characteristics, specifies a unique operating point at where the possible maximum power point (MPP) is delivered. At the MPP, the PV array operates at maximum power efficiency. In order to continuously harvest maximum power at any point of time from solar PV modules, a good MPPT algorithms need to be employed. Currently, due to its simplicity and easy implementation, Perturb and Observe (P&O) algorithms are the most commonly used MPPT control method in the PV systems but it has a drawback at suddenly varying environment situations, due to constant step size. In this paper, to overcome the difficulties of the fast changing environment and suddenly changing the power of PV array due to constant step size in the P&O algorithm, least mean Square (LMS) methods is proposed together with P&O MPPT algorithm which is superior to traditional P&O MPPT. PV output power is predicted using LMS method to improve the tracking speed and deduce the possibility of misjudgment of increasing and decreasing the PV output. Simulation results shows that the proposed MPPT technique can track the MPP accurately as well as its dynamic response is very fast in response to the change of environmental parameters in comparison with the conventional P&O MPPT algorithm, and improves system performance.

Location-Based Services(LBS) is a service that provide location information by using communication network or satellite signal. In order to provide LBS precisely and efficiently, we studied how we can reduce the error on location determination of objects such people and things. We focus on using the least square method and triangulation positioning method to improves the accuracy of the existing location determination method. Above two methods is useful if the distance between the AP and the tags can be find. Though there are a variety of ways to find the distance between the AP and tags, least squares and triangulation positioning method are wildely used. In this thesis, positioning method is composed of preprocessing and calculation of location coordinate and detail of methodology in each stage is explained. The distance between tag and AP is adjusted in the preprocessing stage then we utilize least square method and triangulation positioning method to calculate tag coordinate. In order to confirm the performance of suggested method, we developed the test program for location determination with Labview2010. According to test result, triangulation positioning method showed up loss error than least square method by 38% and also error reduction was obtained through adjustment process and filtering process. It is necessary to study how to reduce error by using additional filtering method and sensor addition in the future and also how to improve the accuracy of location determination at the boundary location between indoor and outdoor and mobile tag.

본 논문에서는 위치기반서비스의 핵심기능을 담당하는 측위기술 중 흔히 사용되고 있는 삼각측량법과 최소자승법을 보정한 방법을 이용하여 객체의 위치를 결정하는 알고리즘의 산포를 감소시키는 방안을 연구하였다. 두 측위 방법에서 사용되는 거리값은 모두 동일한 보정과 필터링 과정을 적용하였으며, 프로그램 구현 후 실내에서 테스트를 실시하였다. 프로그램은 LabView 2010으로 구현하였고, 각각의 알고리즘을 모듈화하여 필터링 적용 전후 및 개선효과를 비교하기 쉽도록 구성하였다. 일반적인 환경에서 실험한 결과 삼각측량이 최소자승법보다 더 좋은 정확도를 보여주었고, 필터링 과정을 거칠수록 정확도가 향상되는 것을 확인하였다.

To solve the problem that the conventional circle detection algorithm has low processing speed and poor identification accuracy in presence of overlap of objects, a novel multiple circles detection algorithm is proposed. Firstly, the consecutive edges with single pixel are obtained through an edge tracking method. Moreover, the edges of overlaid objects are extracted from the cross section according to the linear projection method. Secondly, a large number of non-circular edges are excluded by utilizing a coarse detection that decides whether four points on an edge are on the same circle or not. Lastly, the circles are recognized by the fine detection according to the geometrical feature which two subarcs belonging to one circle have the same center and radius. The experimental results demonstrate that the algorithm is superior in speed, precision and accuracy, comparing to the conventional ones, such as Hough transform circle detection and randomized circle detection. Furthermore, it can solve the issues from overlap of objects and accurately identify the multiple circular objects in the complex scenes as well. The algorithm is concise, fast and robust.

In this article, aiming at complex prediction problems of the rail transit passenger flow and prediction problems combined with the actual situation of rail transit in Beijing. We will propose a fusion model of passenger flow for predicting. It can improve the prediction accuracy for passenger flow forecasting. We use the partial least squares regression method to solve multicollinearity between the dependent variable. The method of principal component analysis can rescreen the all the factors which are affect the passenger flow. To extract comprehensive variable this has the best ability to explain the passenger flow from all of the information, in order to solve the relevance of statistics, noise and information redundancy. The nonlinear prediction model which is between comprehensive variable and passenger flow will be established. Finally, through the passenger flow forecasting of exchange station of Beijing Metro Line 1 to verify the effectiveness of the method.

Bovine iris recognition technology plays a very important role in meat food traceability system about large-scale livestock individual identification. In order to improve the precision and speed of bovine iris location, iris inner and outer edge location method based on dynamic contour tracking and least square principle ellipse fitting were respectively proposed in the paper, according to the characteristics of bovine iris image. For iris inner edge location, firstly, the pupil centroid was determined, and pupil sub-image was separated from eye image, then, using dynamic contour tracking method based on the non-initialized level set model to track the boundary of pupil, and got iris inner boundary. For iris outer edge location, noise reducing template was determined by pupil sub-image, which combined with mathematical morphology operators to further suppress random noise, so, ideal outer edge detection curve was obtained. Finally, it got iris outer edge of ellipse fitting based on least squares principle. Experimental results shown that this method was less running time, high location accuracy, it has a certain practicality in large-scale livestock meat food traceability.

Prediction of network public opinion is a complicated prediction featuring poor information, small samples and uncertainty. A prediction model of network public opinion based on grey support vector machine (SVM) is specified to increase prediction accuracy. First, network data are preprocessed by text clustering, hotpot extraction and data aggregation. Then a time series model GM(1,1) is established and SVM is used to modify prediction outcomes of GM(1,1). At last, simulation experiment is conducted to test performance of the model. Simulation results indicate that grey SVM improves the prediction accuracy of network public opinion compared with traditional prediction models. The predictions have certain practical values.

This paper proposes the recognition method of the strip shape using the Least-Square method and the distinction method of the asymmetric shape and the compensation method upon the shape control values for the stainless steel cold rolling mill. This paper proposes the shape recognition method before control and the compensation method to minimize the fluctuation of the shape deviation and to get symmetric shape. This paper shows on line test results to verify the performance of the control method for the process. The experiments have been performed with respect to various material type, thickness, and strip width. The performance of the proposed method is obtained excellent quality and high productivity as results.

For Preisach model, Everett function from the transient curves is needed to simulate the hysteresis phenomena. However it becomes very difficult to get the function if the it would be made only from experiments. In this paper, a simple and stable procedure using least square method and logarithm function to determine the Everett function which follows the Gauss distribution for interaction field axis is proposed. The characteristics of the parameters used in this procedure are also presented. The proposed method is applied to implement hysteresis loops. The simulation for hysteresis loop is compared with experiments and good agreements could be shown.

차선검출시스템은 지능형 차량 시스템의 중요한 요소이다. 차선검출 시, 주변 환경과 날씨의 변화 때문에 차선검출은 다양한 어려움에 직면하게 된다. 본 논문에서는 차선검출 및 추적을 위해 다양한 환경에서도 안정적으로 동작하는 간단하면서 효율적인 방법을 제안한다. 제안된 방법에서는 차선을 추적하고 차선의 기울기를 수정하기 위해 확률적 허프 변환(Probabilistic Hough Transform, PHT)과 최소자승법(Least-square method, LSM)를 이용한다. 일반적으로 차량의 내부에 설치된 카메라로부터 획득된 영상은 영상의 하단부분에서 차선이 비교적 뚜렷이 나타나고, 주변의 간섭을 적게 받는다는 가정 하에 제안된 방법에서는 차선검출 및 추적의 효율성을 증대시키기 위해 영상의 하단부분에 관심의 대상이 되는 두 개의 영역을 설정한다. 제안된 방법의 효율성을 입증하기 위해 정지영상과 비디오영상을 사용하여 실험하였고, 실험결과 제안된 방법이 강건하고, 신뢰성있는 결과를 얻었음을 보였다.

A lane detection system is one of the major components of intelligent vehicle systems. Difficulties in lane detection mainly come from not only various weather conditions but also a variety of special environment. This paper describes a simple and stable method for the broken lane tracking in various environments. Probabilistic Hough Transform (PHT) and the Least-square method (LSM) are used to track and correct the lane orientation. For the efficiency of the proposed method, two regions of interest (ROIs) are placed in the lower part of each image, where lane marking areas usually appear with less intervention in our system view. By testing in both a set of static images and video sequences, the experiments showed that the proposed approach yielded robust and reliable results.

This paper proposes a novel approach to determine symmetrical components of power system by applying method of least squares in time domain. For the modern power system stability, clearance of faults on high voltage transmission lines in zero response time is crucial and important. Symmetrical components have a great attention since last century. They have been found an effective tool for the analysis of symmetrical and unsymmetrical faults in power system. Moreover, magnitude of symmetrical components are also used as a caution about faults in system. With rapid changes in technology, Microprocessor assumed to be fastest machine of the modern era. Hence microprocessor based techniques were developed and implemented for last few decades. The proposed technique apply least square method in the computation of symmetrical components which is suitable as an application in microprocessor based monitoring and controlling power system in order to avoid cascading failures. Simulation of proposed model is carried out in MATLAB/SIMULINK and all results exploit the validity of model.

The ordinary least square method (OLS) has been the most frequently used least square method in hydrological data analysis. Its computational algorithm is simple, and the error analysis is also simple and clear. However, the primary assumption of the OLS method, which states that the dependent variable is the only error-contaminated variable and all other variables are error free, is often violated in hydrological data analyses. Recently, a matrix algorithm using the singular value decomposition for the total least square (TLS) method has been developed and used in data analyses as errors-in-variables model where several variables could be contaminated with observational errors. In our study, the algorithm of the TLS is introduced in the evaluation of rating curves between the flow discharge and the water level. Then, the TLS algorithm is applied to real data set for rating curves. The evaluated TLS rating curves are compared with the OLS rating curves, and the result indicates that the TLS rating curve and the OLS rating curve are in good agreement. The TLS and OLS rating curves are discussed about their algorithms and error terms in the study.

LCL filters are widely used in three-phase PWM converter for its advantages of small volume, low cost and inhibition of high frequency current harmonic. However, it is difficult to optimize its design because its parameters are mutually influenced while the value of each parameter for LCL filter has impacts on the converter's cost and size. In this paper, the target of optimization is to minimize the parameter values of LCL filter, and an optimization method for parameters of LCL filter of three-phase PWM converter based on least square method is proposed. With this method, a quantitative calculation of the harmonic component of the converter’s side phase voltage is performed first, and then the quantitative relationship between phase voltage harmonics and grid phase current harmonics is analyzed. After that, the attenuation requirement of each harmonic is obtained by taking into account the requirements for each harmonic component of grid current. Then according to the optimization objective, the objective function with minimum harmonic attenuation deviation is established, and least squares method is adopted for three-dimensional global searching of parameters for LCL filter. Thus, the designed harmonic attenuation curve approximates the minimum attenuation requirements, and the optimized LCL filter parameters are obtained. Finally, the effectiveness of the method is verified by the experiments.

This paper concerns a least square approach to optimizing a thinned antenna array with respect to antenna spacing to improve the sidelobe performance. A least square method based on a modified version of the modified perturbation method is proposed to efficiently synthesize an optimum pattern in a thinned array. It is demonstrated that the array performance improves with the proposed method, compared with the conventional method.

Quantitative Structure-Resolution Relationship (QSRR) using the Comparative Molecular Field Analysis (CoMFA) software was applied to predict the chromatographic behaviors of chiral drugs with an amine moiety on the chiral cellobiohydrolase (CBH) columns. As a result of the Quantitative CoMFA-Resolution Relationship study, using the partial least square method, prediction of the behavior of drugs with amine moiety upon chiral separation became possible from their three dimensional molecular structures. When a mixed mobile phase of 10 mM aqueous phosphate buffer (pH 7.0) - isopropanol (95 : 5) was employed, the best Quantitative CoMFA-Resolution Relationship, derived from the study, provided a cross-validated $q^2$ = 0.933, a normal $r^2$ = 0.995, while the best Quantitative CoMFA-Separation Factor Relationship, also derived from the study, yielded a cross-validated $q^2$ = 0.939, a normal $r^2$ = 0.991. When all of these results are considered, this QSRR-CoMFA analysis appears to be a very useful tool for the preliminary prediction on the chromatographic behaviors of drugs with an amine moiety inside chiral CBH columns.