• 제목/요약/키워드: Conditional Constraints

검색결과 36건 처리시간 0.03초

Interval을 이용한 Conditional Constraints의 Propagation 알고리듬 (A PROPAGATION ALGORITHM FOR INTERVAL-BASED CONDITIONAL CONSTRAINTS)

  • 김경택
    • 대한산업공학회지
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    • 제20권1호
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    • pp.133-146
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    • 1994
  • Conditional constraints are frequently used to represent relations. To use these conditional constraints, it is necessary to develop an appropriate logic in which these conditional constraints can be represented and manipulated. Nevertheless, there has been little research that addresses interval-based conditional constraints. The proposed approach addresses the use of conditional constraints involving intervals in constraint networks. Two algorithms are presented: (1) a propagation algorithm for an interval-based conditional constraint, which is similar to one for an exact-value conditional constraint; (2) a propagation algorithm for interval-based conditional constraints which satisfy some conditions. The former can be applied to any conditional constraint. However, with the former algorithm, conditional constraints are usually categorized into the cases that they cannot be propagated. After investigating several methods in which most conditional constraints can be propagated, we propose the latter algorithm under certain condition that usually results in smaller resulting design space comparing to the former.

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웹 서비스의 선택과 조건 분기에 관한 연구 (A Study on Web Services Selection and Conditional Branches)

  • 서상구
    • 한국IT서비스학회지
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    • 제6권2호
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    • pp.125-143
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    • 2007
  • IT Services market is growing rapidly in the business industry and SOA-based Web Services have been introduced as an effective vehicle for the integration of enterprise-wide applications within organizations. The number of publicly available Web Services is ever increasing recently in a variety of areas, and as the number of public Web Services increases, there will be many Web Services with the same functionality. These services, however, will vary in their QoS properties, such as price, response time and availability, and it is very important to choose a right service while satisfying given QoS constraints. This paper addresses the issue of selecting composite Web Services which involves conditional branches in business processes. It is essential to have any conditional branches satisfy the global QoS constraints at service selection phase, since the branches are chosen to execute at run-time dynamically. We proposed service selection procedures for basic structure of conditional branches and explained them by examples. Experiments were conducted to analyze the impact of the number of candidate services and service types on the time of finding service solutions.

English Conditional Inversion: A Construction-Based Approach

  • Kim, Jong-Bok
    • 한국언어정보학회지:언어와정보
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    • 제15권1호
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    • pp.13-29
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    • 2011
  • Conditional sentences also can be formed by inversion of subject and auxiliary, but it happens only in a limited environment. This paper addresses grammatical constraints in conditional inversion and how they behave differently from the regular conditional clauses based on corpus investigations. Our corpus search reveals many different types of conditional inversion constructions, indicating the difficulties of deriving inverted conditionals from movement operations. In this paper, we provide a construction-based approach to the inverted conditional construction. The paper shows that the most optimal way of describing the general as well as idiosyncratic properties of the inverted conditional constructions is an account in the spirit of construction grammar in which a grammar is a repertory of constructions forming a network connected by links of inheritance.

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조건부 자원 공유를 고려한 스케쥴링 알고리즘 (A scheduling algorithm for conditonal resources sharing consideration)

  • 인지호;정정화
    • 전자공학회논문지A
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    • 제33A권2호
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    • pp.196-204
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    • 1996
  • This paper presents a new scheduling algorithm, which is the most improtant subtask in the high level synthesis. The proposed algorithm performs scheduling in consideration of resource sharing concept based on characteristics of conditionsla bransches in the intermediate data structure. CDFG (control data flow graph) generated by a VHDL analyzer. This algorithm constructs a conditon graph based on time frame of each operation using both the ASAP and the ALAP scheduling algorithm. The conditon priority is obtained from the condition graph constructed from each conditional brance. The determined condition priority implies the sequential order of transforming the CDFG with conditonal branches into the CDFG without conditional branches. To minimize resource cost, the CDFG with conditional branches are transformed into the CDFG without conditonal brancehs according to the condition priority. Considering the data dependency, the hardware constraints, and the data execution time constraints, each operation in the transformed CDFG is assigned ot control steps. Such assigning of unscheduled operations into contorl steps implies the performance of the scheduling in the consecutive movement of operations. The effectiveness of this algorithm is hsown by the experiment for the benchmark circuits.

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Fast Conditional Independence-based Bayesian Classifier

  • Junior, Estevam R. Hruschka;Galvao, Sebastian D. C. de O.
    • Journal of Computing Science and Engineering
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    • 제1권2호
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    • pp.162-176
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    • 2007
  • Machine Learning (ML) has become very popular within Data Mining (KDD) and Artificial Intelligence (AI) research and their applications. In the ML and KDD contexts, two main approaches can be used for inducing a Bayesian Network (BN) from data, namely, Conditional Independence (CI) and the Heuristic Search (HS). When a BN is induced for classification purposes (Bayesian Classifier - BC), it is possible to impose some specific constraints aiming at increasing the computational efficiency. In this paper a new CI based approach to induce BCs from data is proposed and two algorithms are presented. Such approach is based on the Markov Blanket concept in order to impose some constraints and optimize the traditional PC learning algorithm. Experiments performed with the ALARM, as well as other six UCI and three artificial domains revealed that the proposed approach tends to execute fewer comparison tests than the traditional PC. The experiments also show that the proposed algorithms produce competitive classification rates when compared with both, PC and Naive Bayes.

Development of an Item Selection Method for Test-Construction by using a Relationship Structure among Abilities

  • Kim, Sung-Ho;Jeong, Mi-Sook;Kim, Jung-Ran
    • Communications for Statistical Applications and Methods
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    • 제8권1호
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    • pp.193-207
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    • 2001
  • When designing a test set, we need to consider constraints on items that are deemed important by item developers or test specialists. The constraints are essentially on the components of the test domain or abilities relevant to a given test set. And so if the test domain could be represented in a more refined form, test construction would be made in a more efficient way. We assume that relationships among task abilities are representable by a causal model and that the item response theory (IRT) is not fully available for them. In such a case we can not apply traditional item selection methods that are based on the IRT. In this paper, we use entropy as an uncertainty measure for making inferences on task abilities and developed an optimal item selection algorithm which reduces most the entropy of task abilities when items are selected from an item pool.

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No-reference quality assessment of dynamic sports videos based on a spatiotemporal motion model

  • Kim, Hyoung-Gook;Shin, Seung-Su;Kim, Sang-Wook;Lee, Gi Yong
    • ETRI Journal
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    • 제43권3호
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    • pp.538-548
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    • 2021
  • This paper proposes an approach to improve the performance of no-reference video quality assessment for sports videos with dynamic motion scenes using an efficient spatiotemporal model. In the proposed method, we divide the video sequences into video blocks and apply a 3D shearlet transform that can efficiently extract primary spatiotemporal features to capture dynamic natural motion scene statistics from the incoming video blocks. The concatenation of a deep residual bidirectional gated recurrent neural network and logistic regression is used to learn the spatiotemporal correlation more robustly and predict the perceptual quality score. In addition, conditional video block-wise constraints are incorporated into the objective function to improve quality estimation performance for the entire video. The experimental results show that the proposed method extracts spatiotemporal motion information more effectively and predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.

ASIC 설계를 위한 스케쥴링 알고리듬 (A scheduling algorithm for ASIC design)

  • 김기현;정정화
    • 전자공학회논문지A
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    • 제32A권7호
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    • pp.104-114
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    • 1995
  • In this paper, an intermediate representation HSFG(Hanyang Sequential Flow GRaph) and a new scheduling algorithm for the control-dominated ASIC design is presented. The HSFG represents control flow, data dependency and such constraints as resource constraints and timing constraints. The scheduling algorithm minimizes the total operating time by reducing the number of the constraints as maximal as possible, searching a few paths among all the paths produced by conditional branches. The constraints are substitute by subgraphs, and then the number of subgraphs (that is the number kof the constraints) is minimized by using the inclusion and overlap relation among subgraphs. The proposed algorithm has achieved the better results than the previous ones on the benchmark data.

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Rationale of the Maximum Entropy Probability Density

  • Park, B. S.
    • Journal of the Korean Statistical Society
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    • 제13권2호
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    • pp.87-106
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    • 1984
  • It ${X_t}$ is a sequence of independent identically distributed normal random variables, then the conditional probability density of $X_1, X_2, \cdots, X_n$ given the first p+1 sample autocovariances converges to the maximum entropy probability density satisfying the corresponding covariance constraints as the length of the sample sequence tends to infinity. This establishes that the maximum entropy probability density and the associated Gaussian autoregressive process arise naturally as the answers of conditional limit problems.

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유전자 발현량 데이터 증대를 위한 Conditional VAE 기반 생성 모델 (Conditional Variational Autoencoder-based Generative Model for Gene Expression Data Augmentation)

  • 봉현수;오민식
    • 방송공학회논문지
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    • 제28권3호
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    • pp.275-284
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    • 2023
  • 유전자 발현 데이터는 질병의 예후 예측, 약물 반응성 예측 등 질병에 대한 이해와 정밀 의료 실현을 위한 연구들에 활용될 수 있지만 충분한 양의 데이터를 수집하는 데 많은 비용적 문제가 있다. 본 논문에서는 Conditional VAE에 기반한 유전자 발현 데이터 생성 모델을 제안하였다. 이전 연구인 WGAN-GP기반의 유전자 발현 생성 모델과 정형 데이터 생성 모델인 CTGAN, TVAE와 비교하여 본 논문의 Conditional VAE기반 모델이 생물학적, 통계학적으로 더 유의미한 합성 데이터를 생성할 수 있음을 보였다.