• Korean Journal of Cognitive Science
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• v.33 no.1
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• pp.23-50
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• 2022

Source memory is a cognitive process that combines the representation of the origin of the episodic experience with an item. By studying this daily process, researchers have made fundamental discoveries that make up the foundation of brain and behavior research, such as executive function and binding. In this paper, we review and conduct a bibliometric analysis on source memory papers published from 1989 to 2020. This review is based on keyword co-occurrence networks and author citation networks, providing an in-depth overview of the development of source memory research and future directions. This bibliometric analysis discovers a change in the research trends: while research prior to 2010 focused on individuality of source memory as a cognitive function, more recent papers focus more on the implication of source memory as it pertains to connectivity between disparate brain regions and to social neuroscience. Keyword network analysis shows that aging and executive function are continued topics of interest, although frameworks in which they are viewed have shifted to include developmental psychology and meta memory. The use of theories and models provided by source memory research seem essential for the future development of cognitive enhancement tools within and outside of the field of Psychology.

• Korean Journal of Cognitive Science
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• v.29 no.3
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• pp.161-192
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• 2018

Retrieving temporal information of encoded events is one of the core control processes in episodic memory. Despite much prior neuroimaging research on episodic retrieval, little is known about how large-scale connectivity patterns are involved in the retrieval of sequentially organized episodes. Task-related functional connectivity multivariate pattern analysis was used to distinguish the different sequential retrieval. In this study, participants performed temporal episodic memory tasks in which they were required to retrieve the encoded items in either the forward or backward direction. While separately parsed local networks did not yield substantial efficiency in classification performance, the large-scale patterns of interactivity across the cortical and sub-cortical brain regions implicated in both the cognitive control of memory and goal-directed cognitive processes encompassing lateral and medial prefrontal regions, inferior parietal lobules, middle temporal gyrus, and caudate yielded high discriminative power in classification of temporal retrieval processes. These findings demonstrate that mnemonic control processes across cortical and subcortical regions are recruited to re-experience temporally-linked series of memoranda in episodic memory and are mirrored in the qualitatively distinct global network patterns of functional connectivity.

• Korean Journal of Cognitive Science
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• v.20 no.4
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• pp.535-554
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• 2009

Information collected on mobile devices might be utilized to support user's memory, but it is difficult to effectively retrieve them because of the enormous amount of information. In order to organize information as an episodic approach that mimics human memory for the effective search, it is required to detect important event like landmarks. For providing new services with users, in this paper, we propose the prediction model to find landmarks automatically from various context log information based on attributed Bayesian networks. The data are divided into daily and weekly ones, and are categorized into attributes according to the source, to learn the Bayesian networks for the improvement of landmark prediction. The experiments on the Nokia log data showed that the Bayesian method outperforms SVMs, and the proposed attributed Bayesian networks are superior to the Bayesian networks modelled daily and weekly.

• The Journal of Society for e-Business Studies
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• v.15 no.2
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• pp.137-166
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• 2010

A virtual team is defined a group of people that use electronic communications for some or all of their interactions with other team members. Because team members of a virtual team are physically and temporally distributed, a team's transactive memory system(TMS) is considered to be crucial for the team's effectiveness and performance. TMS refers to a set of individual memory systems which integrate knowledge possessed by particular members through a shared awareness of who knows what. This paper seeks to understand (1) how a virtual team's TMS influences team performance, and (2) what factors contribute to developing the team's TMS. Given these purposes, through the extensive literature review, we first identified components and antecedents to develop a theoretical model that predicts a virtual team's performance. Using the survey data gathered from 172 virtual teams, this study found that expertise location, coordination, and cognition-based trust which were proposed as three components of TMS positively influenced a virtual team's performance. Furthermore, this study uncovered that perceived media richness, network tie strength, and shared norms significantly influenced the components of TMS, while geographical dispersion did not exert any significant influence on TMS.

• 정보화사회
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• s.101
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• pp.25-34
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• 1996

음성처리(Voice Processing) 시장은 원격통신 산업에서 지속적으로 가장 빠르게 성장하고 있는 분야중 하나로, 지금까지는 전화망에 기초한 통신 관련 음성응용 기술이었다. 그러나 이제는 데이타 네트워크와 PC터미날까지를 포함한 기술로 그 범위가 확대되고 있으며 그 정의도 재정립되어야 한다. 음성프로세싱 기술은 음성 메시지와 자동전화 프로세싱, 디지탈음성 데이타의 기억장치와 검색을 위해 기본 기술을 사용하는 정보엑세스 응용프로그램, 인지와 통합, 전화화된 신호체계, 컴퓨터와 전화의 통합(CTI)등을 포함한다.

• Management & Information Systems Review
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• v.31 no.2
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• pp.61-87
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• 2012

In order to improve the value of individuals and the organization's performance, strenuous efforts have been made on improving their human capital and expanding their social capital by members of the organization. Accordingly, the purpose of this study is to verify how members' intimacy network of an organization affects the organization's performance. In this research, they are verified by setting the characteristic of individuals intimacy network as an independent variable, and the job performance and the degrees of cooperation in the network as dependent variables. The results of this study show as follows. First, the size, strength, approach of intimacy network showed significant results. In particular, the first impression when first saw him becomes an important variable. And, that is affected by the approach of intimacy network. Second, the approach of intimacy network has a high impact on the cooperative behavior and job performance in a group which is formed by relationships through face-to-face contract.

• Journal of KIISE
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• v.44 no.1
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• pp.51-56
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• 2017

The research area for solving question answering (QA) problems using artificial intelligence models is in a methodological transition period, and one such architecture, the dynamic memory network (DMN), is drawing attention for two key attributes: its attention mechanism defined by neural network operations and its modular architecture imitating cognition processes during QA of human. In this paper, we increased accuracy of the inferred answers, by adapting an automatic data augmentation method for lacking amount of training data, and by improving the ability of time perception. The experimental results showed that in the 1K-bAbI tasks, the modified DMN achieves 89.21% accuracy and passes twelve tasks which is 13.58% higher with passing four more tasks, as compared with one implementation of DMN. Additionally, DMN's word embedding vectors form strong clusters after training. Moreover, the number of episodic passes and that of supporting facts shows direct correlation, which affects the performance significantly.

• Korean Journal of Cognitive Science
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• v.33 no.2
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• pp.109-133
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• 2022

Episodic memory consists of a core event and the associated contexts. Although the role of the hippocampus and its neighboring regions in contextual representations during encoding has become increasingly evident, it remains unclear how these regions handle various context-specific information other than spatio-temporal contexts. Using high-resolution functional MRI, we explored the patterns of the medial temporal lobe (MTL) and cortical regions' involvement during the encoding of various types of contextual information (i.e., journalism principle 5W1H): "Who did it?," "Why did it happen?," "What happened?," "When did it happen?," "Where did it happen?," and "How did it happen?" Participants answered six different contextual questions while looking at simple experimental events consisting of two faces with one object on the screen. The MTL was divided to sub-regions by hierarchical clustering from resting-state data. General linear model analyses revealed a stronger activation of MTL sub-regions, the prefrontal lobe (PFC), and the inferior parietal lobule (IPL) during social (Who), behavioral (How), and intentional (Why) contextual processing when compared with spatio-temporal (Where/When) contextual processing. To further investigate the functional networks involved in contextual encoding dissociation, a multivariate pattern analysis was conducted with features selected as the task-based connectivity links between the hippocampal subfields and PFC/IPL. Each social, behavioral, and intentional contextual processing was individually and successfully classified from spatio-temporal contextual processing, respectively. Thus, specific contexts in episodic memory, namely social, behavior, and intention, involve distinct functional connectivity patterns that are distinct from those for spatio-temporal contextual memory.

• Information and Communications Magazine
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• v.31 no.4
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• pp.10-19
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• 2014

미래인터넷 연구가 우리나라에서 본격적으로 시작된 지 8년차에 접어들고 있다. 초기에 미래인터넷의 실체에 대한 다양한 의견들과 clean-slate로 갈 것인지 evolution을 할 것인지에 대한 논란이 계속된 것으로 기억된다. 현 시점에서 그 때 상황을 되돌아 보면 어떤 생각들이 그나마 유사하게 맞는 것이었는지 알 수 있어 흥미롭기까지 하다. 본고에서는 이런 미래인터넷이 태동해서 논의되었던 필요성들을 사물인터넷 혹은 만물인터넷 중심의 초연결사회의 관점에서 조망해 본 후에, 실제적으로 이런 사회를 대비하여 점차 가시화되고 있는 중요한 인프라요소 및 구축 방향을 모색한다. 이를 ICT 인프라 차원에서 다시 바라보면 최근 구축과 운용의 중심이 하드웨어에서 소프트웨어 중심으로 급속하게 전환되는 큰 변화가 본격화하고 있다. 즉 미래 사회가 요구하는 초연결에 기반한 서비스 실증을 개발/운영 병행체제 (DevOps: Developers & Operators)를 통해 신속하고 실질적으로 가능케하고 산업발전을 지원하는 인프라를 통한 개방형 혁신이 가시화되고 있다. 정리하면 본고에서는 미래인터넷으로 시작된 네트워크 인프라의 변화와 현재 현황을 살펴보고 어떤 방법론과 체계에 의하여 빠르게 발전하는 초연결사회의 요구사항을 수용하면서 서로 협업할 수 있고 경제발전을 견인하는 인프라로서의 기능과 역할을 담당할 수 있는지에 대하여 논하고자 한다.

• Journal of Gifted/Talented Education
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• v.27 no.1
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• pp.17-35
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• 2017

The purpose of this study is to analyze the learning objectives characteristics of educational programs of centers for the university affiliated science-gifted education using semantic network analysis, we examined the applicability of semantic network analysis in analyzing learning objectives by comparing the results of analysis with Bloom's revised taxonomy. For this purpose, 702 learning objectives presented in 169 science subjects were selected as subjects to be analyzed. After classifying and coding the learning objectives according to Bloom's revised taxonomy, we conducted a semantic network analysis to investigate the relationship between learning objectives. The results of the analysis are as follows. First, we looked at the number of learning objectives used for each subject, and about 3 elementary school levels and about 6 middle school levels were used. Second, the knowledge dimension such as 'factual and conceptual knowledge' and cognitive process dimension such as 'remember', 'understand', and 'create' was high regardless of the research method and school level. Third, the results of analysis based on the weighting through the semantic network analysis method, the elementary school level emphasize activities th be applied to the actual experimental process through learning about scientific facts, while the middle school level emphasize the understanding of scientific facts and concepts themselves. As a result, it can be seen that the semantic network analysis can analyze characteristics of various learning objectives rather than the conventional simple statistical analysis.