• 대한수학회보
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• 제55권5호
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• pp.1483-1490
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• 2018

In this note, it is proven that the slice Bergman kernels for some axially symmetric slice domains are zero-free by a simple method.

• 호남수학학술지
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• 제43권4호
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• pp.691-700
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• 2021

In this paper, we compute directly the Hankel matrix representation of the Hankel operator on the Hardy space of the unit disc without using any classical kernel functions with respect to special orthonormal bases for the Hardy space and its orthogonal complement. This gives an elementary proof for the formula.

• Journal of Information Processing Systems
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• 제12권3호
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• pp.436-454
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• 2016

This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected based on the HTC One X hardware platform. We considered various setting factors, such as Bluetooth, brightness, 3G, GPS, Wi-Fi, and Sync. The battery levels for each possible state vector were measured, and then we constructed the battery prediction model using different regression functions based on the collected data. The accuracy of the constructed models using the multi-layer perceptron (MLP) and the support vector machine (SVM) were compared using varying kernel functions. Various parameters for MLP and SVM were considered. The measurement of prediction efficiency was done by the mean absolute error (MAE) and the root mean squared error (RMSE). The experiments showed that the MLP with linear regression performs well overall, while the SVM with the polynomial kernel function based on the linear regression gives a low MAE and RMSE. As a result, we were able to demonstrate how to apply the derived model to predict the remaining battery charge.

• 한국게임학회 논문지
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• 제1권1호
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• pp.61-67
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• 2001

This paper describes a program which learns good strategies for two-poison, deterministic, zero-sum board games of perfect information. The program learns by simply playing the game against either a human or computer opponent. The results of the program's teaming of a lot of games are reported. The program consists of search kernel and a move generator module. Only the move generator is modified to reflect the rules of the game to be played. The kernel uses a temporal difference procedure combined with a backpropagation neural network to team good evaluation functions for the game being played. Central to the performance of the program is the search procedure. This is a the capture tree search used in most successful janggi playing programs. It is based on the idea of using search to correct errors in evaluations of positions. This procedure is described, analyzed, tested, and implemented in the game-teaming program. Both the test results and the performance of the program confirm the results of the analysis which indicate that search improves game playing performance for sufficiently accurate evaluation functions.

• 한국정보통신학회논문지
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• 제11권8호
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• pp.1528-1534
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• 2007

본 논문은 지능형 Gadget 시스템의 개발환경 구현에 관한 논문이다. 지능형 Gadget 시스템에서 사용된 임베디드시스템 응용 프로그램과 리눅스 커널의 구조 및 동작에 대해 논하고 지능형 Gadget 시스템에 필요한 기능 및 구성 요소에 대해 조사 및 분석을 통한 리눅스 커널과의 동작 및 기능 검증 구현을 보인다. 새로운 지능형 임베디드 시스템의 하나인 Gadget 시스템에 적용 가능하도록 요구되는 기능과 동작을 구현하고 새로운 소형 운영 체제를 위한 개발에 적용 가능하다. 그러한 소형 운영체제는 지능형 개인정보서비스를 위한 임베디드 Gadget 시스템으로써 지능형 정보화 기능을 지원하고 새로운 소형 운영 체제를 탑재한 시스템의 개발에 적용 가능하다. 본 논문에서는 그러한 지능형 임베디드 Gadget 시스템과 응용 개발을 위한 개발환경 구현에 대하여 기술한다.

• 전기학회논문지
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• 제58권2호
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• pp.399-406
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• 2009

In this study, Polynomial Radial Basis Function Neural Network(pRBFNN) based on Fuzzy Inference System is designed and its parameters such as learning rate, momentum coefficient, and distributed weight (width of RBF) are optimized by means of Particle Swarm Optimization. The proposed model can be expressed as three functional module that consists of condition part, conclusion part, and inference part in the viewpoint of fuzzy rule formed in 'If-then'. In the condition part of pRBFNN as a fuzzy rule, input space is partitioned by defining kernel functions (RBFs). Here, the structure of kernel functions, namely, RBF is generated from HCM clustering algorithm. We use Gaussian type and Inverse multiquadratic type as a RBF. Besides these types of RBF, Conic RBF is also proposed and used as a kernel function. Also, in order to reflect the characteristic of dataset when partitioning input space, we consider the width of RBF defined by standard deviation of dataset. In the conclusion part, the connection weights of pRBFNN are represented as a polynomial which is the extended structure of the general RBF neural network with constant as a connection weights. Finally, the output of model is decided by the fuzzy inference of the inference part of pRBFNN. In order to evaluate the proposed model, nonlinear function with 2 inputs, waster water dataset and gas furnace time series dataset are used and the results of pRBFNN are compared with some previous models. Approximation as well as generalization abilities are discussed with these results.

• 호남수학학술지
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• 제46권2호
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• pp.313-334
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• 2024

In the current study, our aim is to define new generalized extended beta and hypergeometric types of functions. Next, we methodically determine several integral representations, Mellin transforms, summation formulas, and recurrence relations. Moreover, we provide log-convexity, Turán type inequality for the generalized extended beta function and differentiation formulas, transformation formulas, differential and difference relations for the generalized extended hypergeometric type functions. Also, we additionally suggest a generating function. Further, we provide the generalized extended beta distribution by making use of the generalized extended beta function as an application to statistics and obtaining variance, coefficient of variation, moment generating function, characteristic function, cumulative distribution function, and cumulative distribution function's complement.

• 전기전자학회논문지
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• 제13권4호
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• pp.1-7
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• 2009

본 논문에서는 고정되지 않은 배경의 동영상에서 객체를 추출하는 방법을 제안한다. 제안하는 알고리즘은 추적에 기반을 둔 기법으로 크게 세 단계의 과정으로 이루어져 있다. 첫 번째 단계는 초기 분할로서, 사용자의 반응을 이용하여 첫 프레임의 분할 결과를 획득하는 과정이다. 초기 분할을 통해 획득된 결과 샘플은 커널 밀도 추정을 이용하여 각 매크로 블록별 컬러 확률 밀도 함수를 생성하는데 사용된다. 두 번째 단계에서는 각 프레임에 대해 이전 프레임의 경계 정보와 움직임 벡터를 이용하여 일치성 띠를 생성하고, 생성된 띠에 대한 시공간 확률을 추정한다. 마지막 단계에서는 각 픽셀별 컬러, 시공간, 스무드항의 합으로 구성된 에너지 함수를 최소화하여 최종 결과를 획득한다. 실험 결과를 통해서 본 논문에서 제안하는 기법이 정확한 분할 결과를 추출하는 지 다양한 테스트 영상을 통해 확인한다.

• 제어로봇시스템학회논문지
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• 제3권4호
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• pp.373-380
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• 1997

In order to implement the real-time operating systems for robot controller, this paper proposes a systematic method for implementing the real-time kernel under the DOS environment. So far, we designed the robot control software and its own operating system simultaneously. Though robot operating systems have simple structure, it allows the developer to have a surplus time and effort to implement complete robot systems. In addition to this, in most cases of this type, operating systems does not support multitasking function, thus, low level hardware interrupts are used for real-time execution. Subsequently, some kinds of real-time tasks are hard to implement under this environment. Nowadays, the operating systems for robot controller requires multitasking functions, intertask communication and task synchronization mechanism, and rigorous real-time responsiveness. Thus, we propose an effective and low costs real-time systems for robot controller satisfying the various real-time characteristics. The proposed real-time systems are verified through real implementation.

• 한국컴퓨터산업학회논문지
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• 제7권1호
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• pp.47-56
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• 2006

혈액에서 추출된 프로테옴 패턴(단백질 DNA 정보)는 인간 신체 기관의 병리학적 상태를 잠재적으로 반영하고 있다. 신체기관의 질병이나 이상은 이러한 프로테옴 패턴의 분석에 의해 식별될 수 있다고 알려져 있으며 프로테옴 패턴 정보를 분석하는 여러 가지 방법들이 현재 존재하고 있다. 본 논문에서는 SVM(Support Vector Machine)과 GA(Genetic Algoritm)의 융합에 근거하여 암 진단을 위한 디시전 모델의 효과적 학습(learning) 방법을 제안한다. <중략> 그 결과로서 개별적 kernel function 들보다 더 우수한 분류성능을 갖는 최적의 디시전 모델이 얻어졌다. 위암 데이터 셋 과 두 개의 일반 데이터 셋(대장암, 백혈병)을 사용한 컴퓨터 실험에서 제안된 방법이 다른 Kernel function 들에 비해 더 우수한 분류 성능을 보여주었다.