• Korean Journal of Child Studies
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• v.25 no.6
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• pp.105-115
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• 2004

The 60 subjects of this study were 3rd, and 6th grade elementary and undergraduate university students. The instrument of 44 items had two typical and two atypical exemplars from 11 semantic categories. Each subject was exposed individually to the word list and asked to categorize each item. At test, subjects generated five items that came to mind in each category. Data was analyzed by 2-way ANOVA, age (3) $\times$ category of typicality (2). All main effects and the interaction effect between age and typicality were significant. There were no significant differences among age groups on typical lists while significant differences between university and elementary school students (Grades 3 and 6) were found on atypical lists. Thus, the knowledge base might be an important factor in implicit memory.

• Annual Conference on Human and Language Technology
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• 1999.10e
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• pp.335-342
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• 1999

The experiments reported here investigated whether seeing a speaker's face (visible speech) affects the perception and memory of Korean speech sounds. In order to exclude the possibility of top-down, knowledge-based influences on perception and memory, the experiments tested people with no knowledge of Korean. The first experiment examined whether visible speech (Auditory and Visual - AV) assists English native speakers (with no knowledge of Korean) in the detection of a syllable within a Korean speech phrase. It was found that a syllable was more likely to be detected within a phrase when the participants could see the speaker's face. The second experiment investigated whether English native speakers' judgments about the duration of a Korean phrase would be affected by visible speech. It was found that in the AV condition participant's estimates of phrase duration were highly correlated with the actual durations whereas those in the AO condition were not. The results are discussed with respect to the benefits of communication with multimodal information and future applications.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.60-63
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• 2011

프로그램 코드는 실행이 되기 전에 반드시 주 기억 장치에 Loading 되어야 하는데, 이때 Loading Time 은 압축 데이터를 NAND Flash Memory 로부터 읽어오는 시간과 압축을 복원하는 시간의 합이 된다. 따라서 빠른 압축 복원 속도는 코드 압축을 사용하는 임베디드 장치에서는 매우 중요한 요소가 된다. 일반적으로 휴대 장치의 경우 일반 PC 와는 달리 적은 배터리 용량 및 프로세서의 한계, 프로그램을 저장하는 NAND Flash Memory 의 크기 때문에 최적의 성능을 발휘할 수 없었다. 본 논문에서는 무 손실 압축 알고리즘에 대한 연구를 진행 함과 동시에 모바일 환경에 적합한 LZCode 을 개선하여 복원속도를 기존 LZCode 보다 1.5 배 향상 시키는 알고리즘을 제시 하고자 한다.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.4
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• pp.391-406
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• 2014

The performance of General-Purpose computation on Graphics Processing Units (GPGPU) is heavily dependent on the memory access behavior. This sensitivity is due to a combination of the underlying Massively Parallel Processing (MPP) execution model present on GPUs and the lack of architectural support to handle irregular memory access patterns. Application performance can be significantly improved by applying memory-access-pattern-aware optimizations that can exploit knowledge of the characteristics of each access pattern. In this paper, we present an algorithmic methodology to semi-automatically find the best mapping of memory accesses present in serial loop nest to underlying data-parallel architectures based on a comprehensive static memory access pattern analysis. To that end we present a simple, yet powerful, mathematical model that captures all memory access pattern information present in serial data-parallel loop nests. We then show how this model is used in practice to select the most appropriate memory space for data and to search for an appropriate thread mapping and work group size from a large design space. To evaluate the effectiveness of our methodology, we report on execution speedup using selected benchmark kernels that cover a wide range of memory access patterns commonly found in GPGPU workloads. Our experimental results are reported using the industry standard heterogeneous programming language, OpenCL, targeting the NVIDIA GT200 architecture.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.9-31
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• 2023

This study is a study on the different cognitive systems and different knowledge systems of members participating in complex and diverse consulting projects, and it is a study on team collaboration that affects the team performance of the project. The purpose of this study is to analyze the mediating effects of team shared cognition, team transactive memory, team knowledge integration, and team efficacy in the cognitive interaction process of a consulting project. This study established a research model and research hypothesis based on previous studies. Data were collected from consultants who actually participated in the consulting project. To empirically analyze the research hypothesis, demographic analysis, validity and reliability analysis, structural model analysis for hypothesis verification, and mediating effect analysis using phantom variables were performed. As a result of the study, in order to increase team performance, it is necessary to improve team shared cognition and team transactive memory, which are cognitive systems, and team knowledge integration, which is a knowledge system, must also be improved. Therefore, there is a need for a sense of team efficacy that integrates disparate cognitive and knowledge systems, trusts each other's expertise, and enables successful team work. In addition, future studies on sub-factors of cognitive processes are needed.

• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.43-54
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• 2019

Currently, a majority of artificial intelligence is used to secure big data; however, it is concentrated in a few of major companies. Therefore, automatic data augmentation and efficient learning algorithms for small-scale data will become key elements in future artificial intelligence competitiveness. In addition, it is necessary to develop a technique to learn meanings, correlations, and time-related associations of complex modal knowledge similar to that in humans and expand and transfer semantic prediction/knowledge inference about unknown data. To this end, a neural memory model, which imitates how knowledge in the human brain is processed, needs to be developed to enable knowledge expansion through modality cooperative learning. Moreover, declarative and procedural knowledge in the memory model must also be self-developed through human interaction. In this paper, we reviewed this essential methodology and briefly described achievements that have been made so far.

• The Journal of the Acoustical Society of Korea
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• v.18 no.5
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• pp.44-51
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• 1999

This paper presents a massively parallel computational model for the efficient integration of speech and natural language understanding. The phoneme model is based on continuous Hidden Markov Model with context dependent phonemes, and the language model is based on a knowledge base approach. To construct the knowledge base, we adopt a hierarchically-structured semantic network and a memory-based parsing technique that employs parallel marker-passing as an inference mechanism. Our parallel speech recognition algorithm is implemented in a multi-Transputer system using distributed-memory MIMD multiprocessors. Experimental results show that the parallel speech recognition system performs better in recognition accuracy than a word network-based speech recognition system. The recognition accuracy is further improved by applying code-phoneme statistics. Besides, speedup experiments demonstrate the possibility of constructing a realtime parallel speech recognition system.

• Journal of Intelligence and Information Systems
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• v.5 no.2
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• pp.79-97
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• 1999

Knowledge management (KM) is emerging as a robust management mechanism with which an organization can remain highly intelligent and competitive in a turbulent market. Organization knowledge is at the heart of KM success. As a vehicle of acquiring organizational knowledge in a distributed decision-making environment, we applied a fuzzy cognitive map (FMM) technique and proved its effectiveness in a distributed knowledge management environment. Our approach was applied to the financial statement analysis problem, yielding a robust result.

• The Journal of Information Systems
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• v.25 no.2
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• pp.1-25
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• 2016

Purpose The innovation capability nowadays has become increasingly prominent in the universities not only for schools but also for teachers. However, due to less attention to the knowledge utilization and management, also some objective constraints, which caused the low level of the innovation capacity for our universities teachers under the current development in China. Meanwhile, transactive memory system (TMS) and knowledge sharing are important contents in knowledge management. The combination of both systems will contribute to a much more comprehensive understanding and performance of knowledge management. The purpose of this study is to investigate the structural relationships between TMS, knowledge sharing, and innovation capability among Chinese university teachers' teams, and to propose the practical implication to integrate effectively internal knowledge of the team to improve innovation capability. Design/methodology/approach In order to exam and verify the hypothesis proposed, we developed a questionnaire with 16 survey items, and each item comes with a five-point Likert-type scale. Hyperlink of online questionnaire was shared through WeChat. It's collected 201 responses from 14 universities in China, and the responders are teaching groups' leaders. And all together 191 responses were filtered out as the valid samples. And we analyze the data set and test research hypotheses by using SPSS 22.0 and AMOS 22.0. Findings All hypotheses are supported. The results reveal that knowledge sharing plays an important role in this study as the mediating role. TMS is positively associated with the innovation capability. And the knowledge sharing plays a significant role as mediating value between them, and influences the TMS's effect on innovation capability. It's thus cleared that if our teachers could well communicate, exchange and collaborate with other teachers in the same group, the innovation capability among the teachers would be improved effectively.

• Management & Information Systems Review
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• v.33 no.1
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• pp.99-118
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• 2014

This study is a product launch strategy Preannouncing companies associated with temporal distance( in the near future/ distant future) and prior knowledge level(high knowledge/ low knowledge), the memory - based judgments(Global product judgment/ Discrete product judgment) and the purchase intention appears, the difference between the empirical verification of what was discriminatory. The study, first, Preannouncing main effect of temporal distance on judgments remember the difference between the purchase intention and consistent global product judgment is more discrete product judgment were higher awareness, purchase intention is higher. Second, Preannouncing high level of product knowledge in global product judgment showed that compared to discrete product judgment. In addition, low levels of knowledge than a discrete product judgment that global product judgment and purchase intention shown that a high level of consumer knowledge through systematic information processing and the road leads to higher purchase attitude. Third, Preannouncing according to the temporal distance and level of knowledge about the interaction effect results in the near future in terms of the high level of knowledge consumers global product judgment was higher than the discrete product judgment. On the other hand, a low level of knowledge of conditions in the distant future, consumers are more discrete product judgment recognized global product judgment showed that high.