• Science of Emotion and Sensibility
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• v.26 no.1
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• pp.55-64
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• 2023

This research investigated category-based feature inference when category features were connected in common cause and common effect causal networks. Previous studies that tested feature inference in causal categories showed unique inference patterns depending on causal direction, number of related features, whether the to-be-inferred feature was cause or effect, etc. However, these prior studies primarily focused on inference pattens that arise from causal relations, and few studies directly explored how the effects of causal relations vary depending on causal strength. We tested feature inference in common cause (Expt. 1) and common effect (Expt. 2) causal categories when casual strengths were either strong or weak. To this end, we had participants learn causal categories where features were causally linked and then perform feature inference task. The results showed that causal strengths as well as causal relations had important impacts on feature inference. When causal strength was strong, inference for common cause feature became weaker but that for the common effect feature became stronger. Moreover, when causal strength was strong and common cause was present, inference for the effect features became stronger, whereas the results were reversed in common effect networks. In particular, in common effect networks, casual discounting was more evident with strong causal strength. These results consistently demonstrate that participants consider not only causal relations but also causal strength in feature inference of causal categories.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.473-480
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• 2006

Extraction is tile most important step in global minimization. Its approache is to identify and extract subexpressions, which are multiple-cubes or single-cubes, common to two or more expressions which can be used to reduce the total number of literals in a Boolean network. Extraction is described as either algebraic or Boolean according to the trade-off between run-time and optimization. Boolean extraction is capable of providing better results, but difficulty in finding common Boolean divisors arises. In this paper, we present a new method for Boolean extraction to remove the difficulty. The key idea is to identify and extract two-cube Boolean subexpression pairs from each expression in a Boolean network. Experimental results show the improvements in the literal counts over the extraction in SIS for some benchmark circuits.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.201-206
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• 2012

The indirect-contact ECG measurement is a newly developed method for unconstrained and nonconscious measurement in daily life. This study introduced a new method of electrode circuit design developed for reducing the 60Hz power line noise observed at the indirect-contact ECG measurement. By the introduced common-mode-driven shielding, the voltage of the electrical shield surrounding the capacitive coupling electrode is maintained at the same as the common mode voltage. Though the method cannot reduce the level of common mode voltage itself, that reduces effectively the differential mode noise converted from the common mode voltage by the difference of cloth impedance between the two capacitive coupling electrode. The experiment results using the actual indirect-contact ECG showed that the 60Hz power line noise was reduced remarkably though the reduction ratio was smaller than the expected by the theory. Especially, the reduction ratio became large for the large difference of cloth. It is expected that the introduced method is useful for reducing the power line noise under condition of poor electrical grounding.

• Annual Conference on Human and Language Technology
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• 2004.10d
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• pp.251-258
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• 2004

본 연구는 연결어미가 글 이해와 기억에 미치는 영향을 조사하고, 연결어미의 효과와 글읽기 능력과는 어떤 관련성이 있는지를 조사하기 위해 실시되었다. 연결어미로는 인과 관계와 부가 관계를 나타내는 연결어미가 사용되었다. 앞뒤에 제시되는 두 문장의 국소적 응집성(Local coherence)을 형성하는데 연결어미가 도움을 준다면, 연결어미가 있는 경우에 문장을 이해하는 속도가 빨라지고 글 내용을 기억하는 데에도 도움을 줄 것으로 예측하였다. 만일에 글읽기 능력이 연결어미를 적절히 사용할 수 있는 능력에 의해서도 영향을 받는다면, 연결어미의 출현 여부와 읽기 능력간에 상호작용이 있을 것으로 예측하였다. 실험 1에서는 인과 관계 연결어미를 사용하여 문장 읽기 시간에 연결어미의 출현이 미치는 효과와 문장 회상에 미치는 효과를 조사하였다. 실험 결과, 인과 관계 연결어미는 뒤의 문장을 읽는데 촉진적인 효과를 주었으며, 이런 연결어미의 효과는 읽기 능력에 관계없이 일관된 촉진 효과를 나타냈다. 또한, 연결어미의 출현은 문장의 회상에 도움을 주었으며, 연결어미가 문장 회상에 미치는 효과는 읽기 능력의 상하에 관계없이 일관되게 나타났다. 실험 2에서는 부가 관계 연결어미가 문장 읽기 시간과 회상에 미치는 효과를 조사하였다. 실험 결과. 부가 관계 연결어미 역시 인과 관계 연결어미와 유사한 형태의 효과를 보였다. 실험 1과 실험 2의 결과는 인과 관계와 부가 관계 연결어미가 앞뒤 문장의 응집성 형성에 긍정적인 영향을 주고, 이런 연결어미의 글읽기에 대한 효과는 글읽기 능력에 관계없이 일정하다는 것을 시사한다.건이 복합 명사의 중심어 선택과 의미 결정에 재활용 될 수 있으며, 병렬말뭉치에 의해 반자동으로 구축되는 의미 대역 패턴을 사용하여 데이터 구축의 어려움을 개선하고자 한다. 및 산출 과정에 즉각적으로 활용될 수 있을 것이다. 또한, 이러한 정보들은 현재 구축중인 세종 전자사전에도 직접 반영되고 있다.teness)은 언화행위가 성공적이라는 것이다.[J. Searle] (7) 수로 쓰인 것(상수)(象數)과 시로 쓰인 것(의리)(義理)이 하나인 것은 그 나타난 것과 나타나지 않은 것들 사이에 어떠한 들도 없음을 말한다. [(성중영)(成中英)] (8) 공통의 규범의 공통성 속에 규범적인 측면이 벌써 있다. 공통성에서 개인적이 아닌 공적인 규범으로의 전이는 규범, 가치, 규칙, 과정, 제도로의 전이라고 본다. [C. Morrison] (9) 우리의 언어사용에 신비적인 요소를 부인할 수가 없다. 넓은 의미의 발화의미(utterance meaning) 속에 신비적인 요소나 애정표시도 수용된다. 의미분석은 지금 한글을 연구하고, 그 결과에 의존하여서 우리의 실제의 생활에 사용하는 $\ulcorner$한국어사전$\lrcorner$ 등을 만드는 과정에서, 어떤 의미에서 실험되었다고 말할 수가 있는 언어과학의 연구의 결과에 의존하여서 수행되는 철학적인 작업이다. 여기에서는 하나의 철학적인 연구의 시작으로 받아들여지는 이 의미분석의 문제를 반성하여 본다.반인과 다르다는 것이 밝혀졌다. 이 결과가 옳다면 한국의 심성 어휘집은 어절 문맥에 따라서 어간이나 어근 또는 활용형 그 자체로 이루어져

• Korean Journal of Cognitive Science
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• v.26 no.3
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• pp.279-300
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• 2015

Present research was carried out on the level of exploration to verify that good luck increases probabilistic framing effect but bad luck decrease the effect. And we organized an experiment that designed experience of luck (good luck vs. bad luck vs. control) ${\times}$ probabilistic frame (high vs. low) and observed whether people response based on probabilistic frame or not. As a result, we observed the two-way interaction where experience of good luck increased probabilistic framing effect, while experience of bad luck decreased the effect (Figure 1). We expect to see more studies of contextual framing effect besides probabilistic frame (e.g., positive vs. negative; loss related to context vs. loss irrelevant to context).

• Journal of Environmental Policy
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• v.12 no.3
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• pp.123-159
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• 2013

We use a multi-regional dynamic computable general equilibrium model to explain an economic effect of $CO_2$ tax on the national and regional economy of Korea. First, we compare two $CO_2$ taxes: a region-specific $CO_2$ tax and a uniform $CO_2$ tax. In the region-specific tax, the $CO_2$ tax rate in the capital area and the south-eastern region is much greater than those in other regions. GDP loss resulting from the region-specific tax is bigger than that in the uniform tax. Second, we consider three options for tax recycling: consumption tax recycling, labor-income tax recycling, and corporate-income tax recycling. The corporate-income tax recycling has the least GDP-loss effect over the three options. These results support that it is more efficient to use a uniform $CO_2$ tax rate than a region-specific $CO_2$ tax rate and that the corporate-income tax recycling is more desirable in a sense of efficiency than the consumption and labor-income tax recycling options.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.3
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• pp.310-323
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• 2023

Urbanization and income distribution issues are global interest, and the results of studies on the impact of urbanization on income inequality are different for each country and period. This study analyzes the impact of urbanization on income inequality using regional data from 2000-2021. In particular, serial correlation, spatial dependence, and common factor effects of the Gini coefficient are confirmed and analyzed through a dynamic spatial panel regression model. As a result, urbanization has a positive effect on reducing income inequality. Therefore, it is necessary to continuously promote regional urbanization to improve the income distribution problem. Areas with already high urbanization rates should reduce income inequality by narrowing the wage gap by expanding training opportunities for low-skilled workers, and need to come up with measures to prevent counter-urbanization.

• Proceedings of the KAIS Fall Conference
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• 2004.11a
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• pp.131-133
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• 2004

이 논문에서는 MPEG audio 알고리즘의 필터뱅크를 덧셈을 사용하여 저전력으로 구현할 수 있는 구조를 제안하였다. 제안된 구조는 CSD(Canonic Signed Digit) 형의 계수를 사용하며, 입력신호 샘플을 최대로 공유함으로서 사용되는 덧셈기의 수를 최소화하였다. 제안된 구조는 알고리즘에서 사용된 공통입력 공유, 선형위상 대칭 필터계수를 이용한 공유, 공통입력을 이용한 블록 공유, CSD 형의 계수와 공통패턴 공유를 통하여 사용되는 덧셈의 수를 최소화할 수 있음을 보였다. Verilog-HDL 코딩을 통하여 시뮬레이션을 수행한 결과, 제안된 구조는 기존의 곱셈기 구조의 구현면적과 비교하여 $59.6\%$를 감소시킬 수 있음을 보였다. 또한 제안된 구조의 전력소모도 곱셈기 구조와 비교하여 $59.6\%$를 감소시킬 수 있음을 보였다. 따라서 곱셈기가 내장된 DSP 프로세서를 사용하지 않고도, Arithmetic Unit나 마이크로프로세서를 사용하여 효과적으로 MPEG audio 필터뱅크를 구현할 수 있음을 보였다.

• 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.

• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.658-672
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• 2020

The purpose of this study is to empirically compare statistical models for pre-service teachers' help networks. We identified similarities and differences based on the results of the binary and valued ERGM. Research questions are as follows: First, what are the similarities of factors influencing the binary/valued help network for pre-service teachers? Second, what are differences of factors influencing the binary/valued help network for pre-service teachers? We measured 42 pre-service teachers with focus on their help and friend networks, happiness, and personal characteristics. Results indicated that, first, the similar factors influencing the binary and valued help network of pre-service teachers were local dependencies (reciprocity, transitivity), similarity (major, gender), activity (early childhood education, negative emotion), popularity (early childhood education) and multiplicity (friend network). Second, the difference between factors affecting pre-service teacher's binary and valued help network was the effect of activity (physical education) and popularity (GPA, negative emotion). Based on these findings, we presented implications.