• Electronics and Telecommunications Trends
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• v.35 no.6
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• pp.137-149
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• 2020

Several multi-agent reinforcement learning (MARL) algorithms have achieved overwhelming results in recent years. They have demonstrated their potential in solving complex problems in the field of real-time strategy online games, robotics, and autonomous vehicles. However these algorithms face many challenges when dealing with massive problem spaces in sparse reward environments. Based on the centralized training and decentralized execution (CTDE) architecture, the MARL algorithms discussed in the literature aim to solve the current challenges by formulating novel concepts of inter-agent modeling, credit assignment, multiagent communication, and the exploration-exploitation dilemma. The fundamental objective of this paper is to deliver a comprehensive survey of existing MARL algorithms based on the problem statements rather than on the technologies. We also discuss several experimental frameworks to provide insight into the use of these algorithms and to motivate some promising directions for future research.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.699-707
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• 2015

Although digit character recognition has got a significant improvement in recent years, it is still challenging to achieve satisfied result if the data contains an amount of distracting factors. This paper proposes a novel digit character recognition approach using a multi-layer hierarchical model, Hybrid Restricted Boltzmann Machines (HRBMs), which allows the learning architecture to be robust to background distracting factors. The insight behind the proposed model is that useful high-level features appear more frequently than distracting factors during learning, thus the high-level features can be decompose into hybrid hierarchical structures by using only small label information. In order to extract robust and compact features, a stochastic 0-1 layer is employed, which enables the model's hidden nodes to independently capture the useful character features during training. Experiments on the variations of Mixed National Institute of Standards and Technology (MNIST) dataset show that improvements of the multi-layer hierarchical model can be achieved by the proposed method. Finally, the paper shows the proposed technique which is used in a real-world application, where it is able to identify digit characters under various complex background images.

• Journal of The Korean Association of Information Education
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• v.11 no.2
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• pp.177-184
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• 2007

The purpose of this paper is to evaluate the computer education experience of high school graduates that were taught under the 7th curriculum and present insight into the making of required computer course for college. To achieve this purpose questionnaires were given to college freshmen to fill out about computer education performed not only during middle school, but also outside of the classroom. For suggestions towards computer courses for college students, how students are being taught the use of computers, how students are using computers, and how the computer proficiency of the students were assessed. Considering the results of the analysis of computer education experiences, this study suggests a guiding principle in freshmen's computer education.

• Journal of Educational Research in Mathematics
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• v.11 no.2
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• pp.239-256
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• 2001

The notion of metaphor has been increasingly popular in research of mathematics education. In particular, metaphor becomes a useful unit for analysis to provide a profound insight into mathematical reasoning and problem solving. In this context, this paper takes metaphor as an analytic unit to examine the relationship between objectivity and subjectivity in mathematical reasoning. Specifically, the discourse analysis focuses on the code switching between literal language and metaphor in mathematical discourse. It is shown that the linguistic code switching is parallel with the switching between two different kinds of mathematical knowledge, that is, factual knowledge and mathematical imagination, which constitute objectivity and subjectivity in mathematical reasoning. Furthermore, the pattern of the linguistic code switching reveals the dialectical relationship between the two poles of mathematical reasoning. Based on the understanding of the dialectical relationship, this paper provides some educational implications. First, the code-switching highlights diverse aspects of mathematics learning. Learning mathematics is concerned with developing not only technicality but also mathematical creativity. Second, the dialectical relationship between objectivity and subjectivity suggests that teaching and teaming mathematics is socioculturally constructed. Indeed, it is shown that not all metaphors are mathematically appropriated. They should be consistent with the cultural model of a mathematical concept under discussion. In general, this sociocultural perspective on mathematical metaphor highlights the sociocultural organization of teaching and loaming mathematics and provides a theoretical viewpoint to understand epistemological diversities in mathematics classroom.

• Fashion, Industry and Education
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• v.15 no.1
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• pp.44-58
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• 2017

The purpose of this research is to explore how Millennials mitigate perceived risks that occur during online apparel purchasing decisions through social interactions based on social learning theory. Also, this research investigates concerns generated from interactions with others when consuming apparel online. An exploratory investigation was undertaken with 78 undergraduate students using an online survey that included open and closed questions. Qualitative data revealed positive relationships between consumers' social interactions and purchases of apparel products online. Specifically, information searches through social interactions with trusted individuals utilizing online channels were found to validate purchasing decisions and alleviate perceived risks with purchasing apparel products online. However, consumers were also concerned with certain interactions due to the lack of credibility regarding reviewers, channels, and conflicting information. These findings provide an insight into millennial consumers' learning processes through consumer-to-consumer interactions in social media environments for apparel purchases. As online and mobile shopping along with consumers' social media usage for interacting continue to increase, these research findings guide retailers how to turn their attention to investing and utilizing these channels to enhance millennial consumers' positive purchasing experiences online.

• Korean Institute of Interior Design Journal
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• v.16 no.4
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• pp.119-126
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• 2007

A prototype design process visualization and guidance system, is being developed. Its purpose is to visualize the design process in more intuitive manner so that one can get an insight to the complicated aspects of the design process. By providing a tangible utility to the design process performed by the expert designers or guided by the system, novice designers will be greatly helped to learn how to approach a certain class of design. Not only as an analysis tool to represent the characteristics of the design process, the system will be useful also for learning design process. A design ontology is being developed to provide the system with a knowledge-base, representing designer's activities associated with various design information during the conceptual design process, and then to be utilized for a computer environment for design analysis and guidance. To develop the design ontology, a conceptual framework of design activity model is proposed, and then the model has been tested and elaborated through investigating the nature of the early conceptual design. A design process representation model is conceptualized based on the ontology, and reflected into the development of the system. This paper presents the development process of the visualization system, modeling of design process ontology, and how the system could be utilized for the analysis and learning of conceptual design methods using computer mediated design support environment.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.4
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• pp.491-505
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• 2019

This study analyzes global fashion clusters to provide insight for the domestic fashion market to form a competitive fashion cluster. We examine formation factors and operation types of the global fashion clusters to understand their characteristics. We also explore the effectiveness of each global fashion cluster by investigating the stage of development in fashion clusters. Fourteen cases of global fashion clusters are collected and analyzed. First, global fashion clusters show three types of formation and operation: self-formation, self-formation & government based development, and government, institute, and enterprise based formation & development. Second, the characteristics of global fashion clusters are based on functions related to space, learning, innovation, network, and knowledge. Third, there are four steps in the development stage of global fashion clusters: professional clusters, industrial clusters, learning clusters and innovative industrial clusters. In particular, innovative industrial clusters, the final stage of development, have high levels of effectiveness in terms of co-growth and collaboration among fashion-related businesses in fashion clusters. The results of this study can help guide the development of local fashion cluster in Korea.

• Electronics and Telecommunications Trends
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• v.36 no.2
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• pp.32-42
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• 2021

The rapid growth of deep-learning applications has invoked the R&D of artificial intelligence (AI) processors. A dedicated software framework such as a compiler and runtime APIs is required to achieve maximum processor performance. There are various compilers and frameworks for AI training and inference. In this study, we present the features and characteristics of AI compilers, training frameworks, and inference engines. In addition, we focus on the internals of compiler frameworks, which are based on either basic linear algebra subprograms or intermediate representation. For an in-depth insight, we present the compiler infrastructure, internal components, and operation flow of ETRI's "AI-Ware." The software framework's significant role is evidenced from the optimized neural processing unit code produced by the compiler after various optimization passes, such as scheduling, architecture-considering optimization, schedule selection, and power optimization. We conclude the study with thoughts about the future of state-of-the-art AI compilers.

• Research in Mathematical Education
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• v.26 no.1
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• pp.1-17
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• 2023

Over the last three decades, there has been an increasingly strong emphasis on group-centered approaches to mathematics teaching. One primary responsibility for teachers who use group-centered instruction is to "check in", or intervene, with groups to monitor group learning and provide mathematical support when necessary. While prior research has contributed valuable insight for successful teacher interventions in mathematics group work, there is a need for more fine-grained analyses of interactions between teachers and students. In this study, we co-conducted research with an exemplary middle grade teacher (Ms. Green) to learn about fine-grained details of her intervention practices, hoping to generate knowledge about successful teacher interventions that can be expanded, replicated, and/or contradicted in other contexts. Analyzing Ms. Green's practices as an exemplary case, we found that she used exceptionally short interventions (35 seconds on average), provided space for student dialogue, and applied four distinct strategies to support groups to make mathematical progress: (1) observing/listening before speaking; (2) using a combination of social and analytic scaffolds; (3) redirecting students to task instructions; (4) abruptly walking away. These findings imply that successful interventions may be characterized by brevity, shared dialogue between the teacher and students, and distinct (and sometimes unnatural) teaching moves.

• Asia Marketing Journal
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• v.15 no.3
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• pp.79-95
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• 2013

New product innovation is a process of embodying new knowledge in a product and technology licensing is getting popular as a means to innovations and introduction of new product to the market in today's competitive global market environment. Incumbents often rely on technology licensing to access new product opportunities created by other firms. Prior research has examined various aspects of technology licensing agreements such as specific contract terms of licensing agreements, e.g., distribution of control rights, exclusivity of licensing agreements, cross-licensing, and the scope of licensing agreements. This study aims to provide answers to an important, but under-researched question: why do some incumbents initiate more licensing agreement for exploratory learning while others do it for exploitative learning along the innovation process? We attempt to extend our knowledge of licensing agreements from an organizational learning perspective. Technology licensing as a specific form of interfirm linkages can be initiated with different learning objectives along the process of new product innovation. The exploratory stages of the innovation process such as discovery or research stages involve extensive searches to create new knowledge or capabilities, whereas the exploitative stages of the innovation process such as application or test stages near the commercialization are more focused on developing specific applications or improving their efficiency or reliability. Thus, different stages of the innovation process generate different types of learning and the resulting technological resources. We examine when incumbents as licensees initiate more licensing agreements for exploratory learning objectives and when more for exploitative learning objectives, focusing on two factors that may influence a firm's formation of exploratory and exploitative licensing agreements: 1) its past radical and incremental innovation experience and 2) its internal investments in R&D and marketing. We develop and test our hypotheses regarding the relationship between a firm's radical and incremental new product experience, R&D investment intensity and marketing investment intensity, and the likelihood of engaging in exploratory and exploitive licensing agreements. Using data collected from various secondary sources (Recap database, Compustat database, and FDA website), we analyzed technology licensing agreements initiated in the biotechnology and pharmaceutical industries from 1988 to 2011. The results of this study show that incumbents initiate exploratory rather than exploitative licensing agreements when they have more radical innovation experience and when they invest in R&D activities more intensively; in contrast, they initiate exploitative rather than exploratory licensing agreements when they have more incremental innovation experience and when they invest in marketing activities more intensively. The findings of this study contribute to the licensing and interfirm cooperation studies. First, this study lays a foundation to understand the organizational learning aspect of technology licensing agreements. Second, this study sheds lights on how a firm's internal investments in R&D and marketing are linked to its tendency to initiate licensing agreements along the innovation process. Finally, the findings of this study provide important insight to managers regarding which technologies to gain via licensing agreements. This study suggests that firms need to consider their internal investments in R&D and marketing as well as their past innovation experiences when they initiate licensing agreements along the process of new product innovation.