• 제목/요약/키워드: Incomplete Information

검색결과 555건 처리시간 0.031초

불완전한 영역이론을 위한 반대개념의 학습 (Learning Opposite Concept for Incomplete Domain Theory)

  • 태강수
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제26권8호
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    • pp.1010-1017
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    • 1999
  • 불완전한 계획 영역 이론은 오류 영역(noisy domain)에서 하나의 상태에 상반된 연산자들이 적용되는 불일치성 문제를 야기할 수 있다. 이 문제를 해결하기 위해서 본 논문은 상태를 기술하기 위해 다치 논리를 도입하여 제어지식으로서의 부정적 선행조건을 학습하는 새로운 방법을 제안한다. 기계에는 알려지지 않은 이러한 제어지식이 인간에게는 반대개념으로 잠재적으로 사용되고 있다. 이러한 잠재된 개념을 학습하기 위해 본 논문은 반대 연산자들로 구성된 사이클을 영역이론으로부터 기계적으로 생성하고, 이 연산자들에 대한 실험을 통해 반대 리터럴(literal)들을 추출한다. 학습된 규칙은 불일치성을 방지하면서 동시에 중복된 선행조건을 제거하여 연산자를 단순화시킬 수 있다.Abstract An incomplete planning domain theory can cause an inconsistency problem in a noisy domain, allowing two opposite operators to be applied to a state. To solve the problem, we present a novel method to learn a negative precondition as control knowledge by introducing a three-valued logic for state description. However, even though the control knowledge is unknown to a machine, it is implicitly known as opposite concept to a human. To learn the implicit concept, we mechanically generate a cycle composed of opposite operators from a domain theory and extract opposite literals through experimenting the operators. A learned rule can simplify the operator by removing a redundant precondition while preventing inconsistency.

A new learning algorithm for incomplete data sets and multi-layer neural networks

  • Bitou, Keiichi;Yuan, Yan;Aoyama, Tomoo;Nagashima, Umpei
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.150-155
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    • 2003
  • We discussed a quantitative structure-activity relationships (QSAR) technique on incomplete data set. We proposed a new solver that used 2 kinds of multi-layer neural networks. One is to compensate the defect data, and another is to evaluate the QSAR. The solver can predict the defects in model QSAR data. By using them, we get very high precision QSAR. It is 5-10 times higher than that of a traditional method. However, in case of anti-cancer Carboquone, the prediction is not so complete. It was about O(3) wrong than the model calculation. The predicted values would have rather large error. It is caused by noisy observations of Carboquone. However, if we used the uncertain predictions, new data are included in QSAR. If not, they were omitted. The effect would not be little. Therefore, we evaluated the QSAR. The results are contrary to the expectation, are not so wrong. We believe that the wrong effect is suppressed by including information of new data.

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Structural identification based on incomplete measurements with iterative Kalman filter

  • Ding, Yong;Guo, Lina
    • Structural Engineering and Mechanics
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    • 제59권6호
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    • pp.1037-1054
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    • 2016
  • Structural parameter evaluation and external force estimation are two important parts of structural health monitoring. But the structural parameter identification with limited input information is still a challenging problem. A new simultaneous identification method in time domain is proposed in this study to identify the structural parameters and evaluate the external force. Each sampling point in the time history of external force is taken as the unknowns in force evaluation. To reduce the number of unknowns for force evaluation the time domain measurements are divided into several windows. In each time window the structural excitation is decomposed by orthogonal polynomials. The time-variant excitation can be represented approximately by the linear combination of these orthogonal bases. Structural parameters and the coefficients of decomposition are added to the state variable to be identified. The extended Kalman filter (EKF) is augmented and selected as the mathematical tool for the implementation of state variable evaluation. The proposed method is validated numerically with simulation studies of a time-invariant linear structure, a hysteretic nonlinear structure and a time-variant linear shear frame, respectively. Results from the simulation studies indicate that the proposed method is capable of identifying the dynamic load and structural parameters fairly accurately. This method could also identify the time-variant and nonlinear structural parameter even with contaminated incomplete measurement.

SSR (Simple Sector Remapper) the fault tolerant FTL algorithm for NAND flash memory

  • Lee, Gui-Young;Kim, Bumsoo;Kim, Shin-han;Byungsoo Jung
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -2
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    • pp.932-935
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    • 2002
  • In this paper, we introduce new FTL(Flash Translation Layer) driver algorithm that tolerate the power off errors. FTL driver is the software that provide the block device interface to the upper layer software such as file systems or application programs that using the flash memory as a block device interfaced storage. Usually, the flash memory is used as the storage devices of the mobile system due to its low power consumption and small form factor. In mobile system, the state of the power supplement is not stable, because it using the small sized battery that has limited capacity. So, a sudden power off failure can be occurred when we read or write the data on the flash memory. During the write operation, power off failure may introduce the incomplete write operation. Incomplete write operation denotes the inconsistency of the data in flash memory. To provide the stable storage facility with flash memory in mobile system, FTL should provide the fault tolerance against the power off failure. SSR (Simple Sector Remapper) is a fault tolerant FTL driver that provides block device interface and also provides tolerance against power off errors.

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카오스 특징 추출에 의한 용접 결함의 초음파 형상 인식 (Ultrasonic Pattern Recognition of Welding Defects Using the Chaotic Feature Extraction)

  • 이원;윤인식;이병채
    • 한국정밀공학회지
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    • 제15권6호
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    • pp.167-174
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    • 1998
  • The ultrasonic test is recognized for its significance as a non-destructive testing method to detect volume defects such as porosity and incomplete penetration which reduce strength in the weld zone. This paper illustrates the defect detection in the weld zone of ferritic carbon steel using ultrasonic wave and the evaluation of pattern recognition by chaotic feature extraction using time series signal of detected defects as data. Shown in the time series data were that the time delay was 4 and the embedding dimension was 6 which indicate the geometric dimension of the subject system and the extent of information correlation. Based on fractal dimension and lyapunov exponent in quantitative chaotic feature extraction, feature value of 2.15, 0.47 is presented for porosity and 2.24, 0.51 for incomplete penetration The precision rate of the pattern recognition is enhanced with these values on the total waveform of defect signal in the weld zone. Therefore, we think that the ultrasonic pattern recognition method of weld zone defects of ferritic carbon steel by ultrasonic-chaotic feature extraction proposed in this paper can boost precision rate further than the existing method applying only partial waveform.

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Prediction Model of Final Project Cost using Multivariate Probabilistic Analysis (MPA) and Bayes' Theorem

  • Yoo, Wi Sung;Hadipriono, FAbian C.
    • 한국건설관리학회논문집
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    • 제8권5호
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    • pp.191-200
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    • 2007
  • This paper introduces a tool for predicting potential cost overrun during project execution and for quantifying the uncertainty on the expected project cost, which is occasionally changed by the unknown effects resulted from project's complications and unforeseen environments. The model proposed in this stuff is useful in diagnosing cost performance as a project progresses and in monitoring the changes of the uncertainty as indicators for a warning signal. This model is intended for the use by project managers who forecast the change of the uncertainty and its magnitude. The paper presents a mathematical approach for modifying the costs of incomplete work packages and project cost, and quantifying reduced uncertainties at a consistent confidence level as actual cost information of an ongoing project is obtained. Furthermore, this approach addresses the effects of actual informed data of completed work packages on the re-estimates of incomplete work packages and describes the impacts on the variation of the uncertainty for the expected project cost incorporating Multivariate Probabilistic Analysis (MPA) and Bayes' Theorem. For the illustration purpose, the Introduced model has employed an example construction project. The results are analyzed to demonstrate the use of the model and illustrate its capabilities.

Partially Observable Markov Decision Processes (POMDPs) and Wireless Body Area Networks (WBAN): A Survey

  • Mohammed, Yahaya Onimisi;Baroudi, Uthman A.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권5호
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    • pp.1036-1057
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    • 2013
  • Wireless body area network (WBAN) is a promising candidate for future health monitoring system. Nevertheless, the path to mature solutions is still facing a lot of challenges that need to be overcome. Energy efficient scheduling is one of these challenges given the scarcity of available energy of biosensors and the lack of portability. Therefore, researchers from academia, industry and health sectors are working together to realize practical solutions for these challenges. The main difficulty in WBAN is the uncertainty in the state of the monitored system. Intelligent learning approaches such as a Markov Decision Process (MDP) were proposed to tackle this issue. A Markov Decision Process (MDP) is a form of Markov Chain in which the transition matrix depends on the action taken by the decision maker (agent) at each time step. The agent receives a reward, which depends on the action and the state. The goal is to find a function, called a policy, which specifies which action to take in each state, so as to maximize some utility functions (e.g., the mean or expected discounted sum) of the sequence of rewards. A partially Observable Markov Decision Processes (POMDP) is a generalization of Markov decision processes that allows for the incomplete information regarding the state of the system. In this case, the state is not visible to the agent. This has many applications in operations research and artificial intelligence. Due to incomplete knowledge of the system, this uncertainty makes formulating and solving POMDP models mathematically complex and computationally expensive. Limited progress has been made in terms of applying POMPD to real applications. In this paper, we surveyed the existing methods and algorithms for solving POMDP in the general domain and in particular in Wireless body area network (WBAN). In addition, the papers discussed recent real implementation of POMDP on practical problems of WBAN. We believe that this work will provide valuable insights for the newcomers who would like to pursue related research in the domain of WBAN.

랜덤 네트워크에 적용 가능한 SBIBD기반의 부하 균형 알고리즘 (An Algorithm of SBIBD based Load Balancing Applicable to a Random Network)

  • 이옥빈;이여진;최동민;정일용
    • 한국멀티미디어학회논문지
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    • 제11권3호
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    • pp.331-340
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    • 2008
  • 부하균형을 위해서는 각 노드의 부하상태 정보가 모든 노드에게 알려져야 하는데 O.Lee[15]가 제안한 SRIBD(Symmetric Balanced Incomplete Block Design) 기반의 부하균형 알고리즘은 노드의 수가 v일 때 2라운드 메시지 교환과 O (${\upsilon}{\sqrt{\upsilon}}$)의 통신오버헤드에 의해 각 노드가 네트워크상의 모든 노드로부터 부하상태 정보를 수신한다. 이 때 각 노드의 통신오버헤드는 O ($\sqrt{\upsilon}$)로서 각 노드가 균등한 오버헤드를 가지며 각 노드가 수신한 정보는 중복이 없다는 점 또한 이 알고리즘의 장점이다. 기술한 바와 같이 이 알고리즘은 매우 효율적이지만 임의의 소수 p에 대하여 노드의 수가 $v=p^2+p+1$일 때만 수행될 수 있다. 이 논문에서는 네트워크상의 노드의 수가 임의의 양의 정수일 때도 이 알고리즘이 동작할 수 있도록 특수한 결합구조를 생성하고자 한다. 이 제안의 성과를 평가하기 위해 노드의 수가 w($5{\leq} w{\leq}5,000$)인 네트워크를 가정하고 각각의 경우에 두 번의 라운드 정보교환으로 최소 80% 이상의 부하상태정보를 수신하도록 실험을 수행한 결과 트래픽오버헤드는 O($w{\sqrt{w}}$) 보다 낮으며 각 노드의 트래픽 오버헤드가 균등하지는 않으나 그 편차가 크지 않은 것으로 나타났다.

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Directional texture information for connecting road segments in high spatial resolution satellite images

  • Lee, Jong-Yeol
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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    • pp.245-245
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    • 2005
  • This paper addresses the use of directional textural information for connecting road segments. In urban scene, some roads are occluded by buildings, casting shadow of buildings, trees, and cars on streets. Automatic extraction of road network from remotely sensed high resolution imagery is generally hindered by them. The results of automatic road network extraction will be incomplete. To overcome this problem, several perceptual grouping algorithms are often used based on similarity, proximity, continuation, and symmetry. Roads have directions and are connected to adjacent roads with certain angles. The directional information is used to guide road fragments connection based on roads directional inertia or characteristics of road junctions. In the primitive stage, roads are extracted with textural and direction information automatically with certain length of linearity. The primitive road fragments are connected based on the directional information to improve the road network. Experimental results show some contribution of this approach for completing road network, specifically in urban area.

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로봇 수술을 위한 3차원 구조계산의 필요성 조사 (Research of 3D Information processing for Robot Surgery)

  • 정재은;최석윤
    • 대한디지털의료영상학회논문지
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    • 제11권1호
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    • pp.43-50
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    • 2009
  • Geometry calculation Using Abdominal internal organ image from traditional laparoscopy or robotic surgery system we can make depth informations through measured 3D structure informations is very helpful to doctors, depth information is mare useful then others that use traditional laparoscopy or robotic surgery system to many doctors. however, traditional method are incomplete. less experienced doctors make much mare prohability of mistake. Hence, 3D information of organ is very helpful to the less experienced doctors. it will be greate role of reducing medical accidents and surgical time. We can get 3D informations using geometrical calculation method in robotic surgical system. also suggested method is needed in traditional surgical method without the need to create a new system, finally, We can get 3D information from traditional system without any new system, it take advantage in cost and create high efficiency. mare information will provided to many doctors.

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