• Title/Summary/Keyword: Causal Condition

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인과적 마코프 조건과 비결정론적 세계

  • Lee, Yeong-Eui
    • Korean Journal of Logic
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    • v.8 no.1
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    • pp.47-67
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    • 2005
  • Bayesian networks have been used in studying and simulating causal inferences by using the probability function distributed over the variables consisting of inquiry space. The focus of the debates concerning Bayesian networks is the causal Markov condition that constrains the probabilistic independence between all the variables which are not in the causal relations. Cartwright, a strong critic about the Bayesian network theory, argues that the causal Markov condition cannot hold in indeterministic systems, so it cannot be a valid principle for causal inferences. The purpose of the paper is to explore whether her argument on the causal Markov condition is valid. Mainly, I shall argue that it is possible for upholders of the causal Markov condition to respond properly the criticism of Cartwright through the continuous causal model that permits the infinite sequence of causal events.

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ALMOST CAUSAL STRUCTURE IN SPACE-TIMES

  • Park, Jong-Chul
    • Journal of the Korean Mathematical Society
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    • v.34 no.2
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    • pp.257-264
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    • 1997
  • We shall introduce the concept of almost causality condition. By defining the almost causality condition we would like to examine the relationship between Woodhouse's causality principle and other known causality conditions. We show that a series of causality conditions can be characterized by using the almost causality condition.

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'Because of Doing' and 'Because of Happening': A Corpus-based Analysis of Korean Causal Conjunctives, -nula(ko) and -nun palamey

  • Oh, Sang-Suk
    • Language and Information
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    • v.8 no.2
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    • pp.131-147
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    • 2004
  • the two Korean causal conjunctive suffixes, -nula(ko) and -nun palamey, based on corpus linguistic analysis. Many of the linguistic accounts available, both in pedagogical reference and in the literature on linguistics, provide incomplete analyses of these suffixes, based on fabricated linguistic data. Using naturally occurring, real linguistic data, this paper examines the syntactic and semantic structures of the two causal suffixes through a consideration of three areas of corpus linguistic analysis: token frequencies, collocations, and semantic prosody. An analysis based on concordance data reveals that the two causal connectives, -nula(ko) and -nun palamey, have more differences than similarities in terms of syntactic and semantic constraints. The idiosyncratic structures of the two suffixes are discussed in terms of same subject condition, verb selection, same agent condition, synchronicity condition, and negative semantic prosody.

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Modeling feature inference in causal categories (인과적 범주의 속성추론 모델링)

  • Kim, ShinWoo;Li, Hyung-Chul O.
    • Korean Journal of Cognitive Science
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    • v.28 no.4
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    • pp.329-347
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    • 2017
  • Early research into category-based feature inference reported various phenomena in human thinking including typicality, diversity, similarity effects, etc. Later research discovered that participants' prior knowledge has an extensive influence on these sorts of reasoning. The current research tested the effects of causal knowledge on feature inference and conducted modeling on the results. Participants performed feature inference for categories consisted of four features where the features were connected either in common cause or common effect structure. The results showed typicality effects along with violations of causal Markov condition in common cause structure and causal discounting in common effect structure. To model the results, it was assumed that participants perform feature inference based on the difference between the probabilities of an exemplar with the target feature and an exemplar without the target feature (that is, $p(E_{F(X)}{\mid}Cat)-p(E_{F({\sim}X)}{\mid}Cat)$). Exemplar probabilities were computed based on causal model theory (Rehder, 2003) and applied to inference for target features. The results showed that the model predicts not only typicality effects but also violations of causal Markov condition and causal discounting observed in participants' data.

Exploring the Impact of Pesticide Usage on Crop Condition: A Causal Analysis of Agricultural Factors

  • Mee Qi Siow;Yang Sok Kim;Mi Jin Noh;Mu Moung Cho Han
    • Smart Media Journal
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    • v.12 no.10
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    • pp.29-37
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    • 2023
  • Human lifestyle is affected by the agricultural development in the last 12,000 years ago. The development of agriculture is one of the reasons that global population surged. To ensure sufficient food production for supporting human life, pesticides as a more effective and economical tools, are extensively used to enhance the yield quality and boost crop production. This study investigated the factors that affect crop production and whether the factors of pesticide usage are the most important factors in crop production using the dataset from Kaggle that provides information based on crops harvested by various farmers. Logistic regression is used to investigate the relationship between various factors and crop production. However, the logistic regression is unable to deal with predictors that are related to each other and identifying the greatest impact factor. Therefore, causal discovery is applied to address the above limitations. The result of causal discovery showed that crop condition is greatly impacted by the estimated insects count, where estimated insects count is affected by the factors of pesticide usage. This study enhances our understanding of the influence of pesticide usage on crop production and contributes to the progress of agricultural practices.

Causal and Intervening Conditions of Korean Immigrants' Sport Participation in the United States

  • KIM, Nam-Su;KIM, Min Soo;SEO, Won Jae
    • Journal of Sport and Applied Science
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    • v.6 no.2
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    • pp.19-25
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    • 2022
  • Purpose: This study attempts to investigate causal and intervening conditions for sport participation of Korean immigrants in the United States. Research design, data, and methodology: Grounded theory approach was used to develop a conceptual framework that presents the psychosocial processes that occur in immigrants' experience of sport participation. Participants were selected purposefully for information-rich cases. Korean immigrants with current experience of having periodically participated in sports were the criterion for sample selection. Based on selection criteria, 9 Korean immigrants took part in interview. The interview discussions were taped and transcribed verbatim into a Word file. The process for data analysis included four grounded theory approaches of purposive and theoretical sampling, an open and axial coding, memo writing, and finally the development of the conceptual framework. Results: Six concepts were revealed in the causal conditions that facilitate the process of immigrants' sport participation in the states: Personal experience, significant others, personality, physical environment, psychological well-being, and social connection. Three concepts were revealed as the intervening conditions that block the process of immigrants' sport participation in the states: Conflict with cultural change of organization, Pressure at workplace, and Economic constraints. Conclusions: Conceptual model presents causal and intervening factors. Further implications were discussed.

Category-based Feature Inference in Causal Chain (인과적 사슬구조에서의 범주기반 속성추론)

  • Choi, InBeom;Li, Hyung-Chul O.;Kim, ShinWoo
    • Science of Emotion and Sensibility
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    • v.24 no.1
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    • pp.59-72
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    • 2021
  • Concepts and categories offer the basis for inference pertaining to unobserved features. Prior research on category-based induction that used blank properties has suggested that similarity between categories and features explains feature inference (Rips, 1975; Osherson et al., 1990). However, it was shown by later research that prior knowledge had a large influence on category-based inference and cases were reported where similarity effects completely disappeared. Thus, this study tested category-based feature inference when features are connected in a causal chain and proposed a feature inference model that predicts participants' inference ratings. Each participant learned a category with four features connected in a causal chain and then performed feature inference tasks for an unobserved feature in various exemplars of the category. The results revealed nonindependence, that is, the features not only linked directly to the target feature but also to those screened-off by other feature nodes and affected feature inference (a violation of the causal Markov condition). Feature inference model of causal model theory (Sloman, 2005) explained nonindependence by predicting the effects of directly linked features and indirectly related features. Indirect features equally affected participants' inference regardless of causal distance, and the model predicted smaller effects regarding causally distant features.

PROPERTIES OF CAUSALLY CONTINUOUS SPACE-TIME

  • Kim, Jong-Chul;Kim, Jin-Hwan
    • Bulletin of the Korean Mathematical Society
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    • v.25 no.2
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    • pp.195-201
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    • 1988
  • In general relativity, analyzing causality is central to the study of black holes, to cosmology, and to each of the major recent mathematical theorems. By causality we refer to the general question of which points in a space-time can be joined by causal curves; relativistically which events can influence (be influenced by) a given event. Various causality conditions have been developed for space-times of the problems associated with examples of causality violations (2, 4). Causally continuous space-times were defined by Hawking and Sachs (5). Budic and Sachs (3) established causal completion. A metrizable topology on the causal completion of a causally continuous space-time was studied by Beem(1). Recently the region of space-time where causal continuity is violated was studied by Ishikawa (6) and Vyas and Akolia (8). In this paper we show characterization for reflectingness in terms of continuity of set valued functions. We investigate some properties of the region related to a causally continuous space-time where distinguishingness is violated, and characterize the chronology condition in terms of distinguishing-violated region.

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Analysis of Performance Factors of Unmanned Aircraft System(UAS)-based Facility Management using Causal Loop Diagram (Causal Loop Diagram을 활용한 무인항공체계 기반 시설물 관리 영향인자 분석)

  • Kwon, Jin-Hyeok;Yu, Chae-Youn;Kim, Sungjin
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2022.04a
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    • pp.85-86
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    • 2022
  • Traditionally, the facility inspection was visually conducted by the managers, and consequently the result can be subjective because of different perspective and experience of them. To solve this problem, the studies on this topic has tried to integrate the UAS. However, it is still concerned to use in practice due to the lack of analysis of the performance factors affecting the UAS-based facility condition inspection. Hence, the purpose of this study is to identify the critical factors as well as their correlations by modeling causal loop diagram (CLD). A total of 20 variables were derived in four categorized groups, and the relationships were analyzed. Further study will develop a system dynamics (SD) model to simulate various scenarios based on stock-flow diagram through the defined relationships in this study.

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Kant's Proof of the Causal Principle (칸트의 인과율 증명)

  • Bae, Jeong-ho
    • Journal of Korean Philosophical Society
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    • v.147
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    • pp.215-237
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    • 2018
  • The purpose of this study is to illuminate the precise nature and the central line of Kant's proof of the causal principle stated in the Second Analogy of the 2nd. edition of the Critique of Pure Reason. The study argues for the following thesis: 1. The proof of the Second Analogy concerns only the causal principle called the "every-event-some-cause" principle, and not the causal law(s) called the "same-cause-same-event" principle. 2. The goal of the proof is to establish the possibility of knowledge of an temporal order of successive states of an object. 3. The proof is broadly an single transcendental argument in two steps. The 1st. step is an analytic argument that infers from the given perceptions of an oder of successive states of an objects to the conclusion that the causal principle is the necessary condition for the objectivity of dies perceived order. The 2nd. step is a synthetic argument that infers from the formal nature of time to the conclusion that the causal principle is a necessary condition for die possibility of objective alterations and of empirical knowledge of these alterations. 4. The poof involves not the 'non sequitur' assumed by P. F. Strawson, that is, Kant infers not directly from a feature of our perceptions to a conclusion regarding the causal relations of distinct states of affairs that supposedly correspond to these perceptions.