• Composites Research
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• v.35 no.5
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• pp.303-308
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• 2022

PIC (Piecewise Integrated Composite) is a new concept for designing a composite structure with mosaically assigning various types of stacking sequences in order to improve mechanical properties of laminated composites. Also, machine learning is a sub-category of artificial intelligence, that refers to the process by which computers develop the ability to continuously learn from and make predictions based on data, then make adjustments without further programming. In the present study, the tapered box beam type PIC robot arm for carrying and transferring wide and thin LCD display was designed based on the machine learning in order to increase structural stiffness. Essential training data were collected from the reference elements, which were intentionally designated elements among finite element models, during preliminary FE analysis. Additionally, triaxiality values for each finite element were obtained for judging the dominant external loading type, such as tensile, compressive or shear. Training and evaluating machine learning model were conducted using the training data and loading types of elements were predicted in case the level accuracy was fulfilled. Three types of stacking sequences, which were to be known as robust toward specific loading types, were mosaically assigned to the PIC robot arm. Henceforth, the bending type FE analysis was carried out and its result claimed that the PIC robot arm showed increased stiffness compared to conventional uni-stacking sequence type composite robot arm.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.3
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• pp.59-66
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• 2022

This study aims to find out how architectural designers applied the design process and what content is applied in the practical process of architectural design in Korea, and to improve it if there is a problem. So the study is carried out by investigating 13 architects(Including one person who wants to keep his work private) with extensive experience in architectural design. The architects were questioned on how and what content the design process was used for their representative works that had been designed. And interviews and field surveys were conducted on other matters to be improved. The survey was conducted from November 2021 to July 2022. According to the conclusion of this study, First, Most architects were applying the design process in the architectural design practice. These are caused by an impact on education, but there was also an aspect of preparation in terms of guidelines such as the Architects Association and storage rights. Second, Although the design process differed in each name and phase, it was generally carried out in the order of the start phase, the planning work phase, the basic design phase, the intermediate design phase, the implementation quarterly, and construction. Third, The step-by-step work of the design process differed slightly depending on the architect, but counseling and contract work were mainly performed at the start-up phase, and field surveys, legal investigations, and case studys were conducted at the planning phase. In the basic design phase, some contents related to architectural programming, basic drawings, images, and models were used as main work contents. In the intermediate design phase, secondary contents such as licensed books and facility facilities were the main tasks. In the implementation design phase, detailed maps and various frost facilities were finally inspected. Since then, construction and supervision have been carried out in the order of progress. Forth, As for the contents to be improved in the future, the architect's ability, the designer's knowledge of the overall architecture, the design supervision system, and the expansion of time for the initial design process were answered.

• The Journal of Korean Philosophical History
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• no.29
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• pp.375-396
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• 2010

The aim of this paper is to suggest some ways of moral education for the building of children's social awareness and relationship skills as social and emotional competencies. Based on the social and emotional learning(SEL), this paper is tried to provide the effective ways to develop children's social awareness and relationship skill. According to SEL, social and emotional competence is the ability to understand, manage, and express the social and emotional aspects of one's life in ways that enable the successful management of life tasks such as learning, forming relationships, solving everyday problems, and adapting to the complex demands of growth and development. And it is also the process of acquiring and effectively applying the knowledge, attitudes, and skills necessary to recognize and manage emotions. Five key competencies such as self-awareness, social awareness, responsible decision making, self-management, relationship skills are taught, practiced, and reinforced through SEL programming. Moral education and social and emotional learning have emerged as two prominent formal approaches used schools to provide guidance for students' behavior. social awareness and relationship skills are necessary for succeeding in school, in the family, in the community, in life in general. Equipped with such skills, attitudes and beliefs, young children are more likely to make healty, caring, ethical, and responsible decisions and to avoid engaging in behaviors with negative consequences such as interpersonal violence and bullying.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.75-99
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• 2012

Innovation can come from inside or outside organizations. Recently, organizations have begun turning to external knowledge more often, through various forms of collective intelligence (CI) as collaborative platform to solve complex problems. Several factors facilitate this CI utilization phenomenon. First, with the rapid development of Internet and social media, numerous web applications have become available to millions of the Internet users over the past few decades. Web 2.0 and social media have become innovative web applications that provide an environment for human social interaction and collaboration. Second, the diffusion of simple and easy-to-use technologies that enable users to interact and design web applications without programming skills have led to vast, previously unknown amounts of user-generated content. Finally, the Internet has enabled communities to connect and collaborate, creating a virtual world of CI. In this study, web enabled CI is defined as a composed ability of individuals who are acting as a single cognitive unit to achieve common goals, think reasonably, solve problems, make decisions, carry out complex tasks, and develop creative ideas collectively through participation and collaboration on the web. Although CI plays a critical role in organizational innovation and collaboration, the dubious quality of CI is still problem that is difficult to solve. In general, the quality level of content collected from the crowd is lower than that from professionals. Thus, it is important to identify determinants of CI quality and to analyze the relationship between CI quality and its usefulness. However, there is a lack of empirical study on the quality factors of web-enabled CI. There exist a variety of web enabled CI sites such as Threadless, iStockphoto or InnoCentive, Wikipedia, and Youtube. One of the most successful forms of web-enabled CI is the Wikipedia online encyclopedia, accessible all over the world. Another one example is Naver KnowledgeiN, a typical and popular CI site offering question and answer (Q&A) services. It is necessary to study whether or not different types of CI have a different effect on CI quality and its usefulness. Thus, the purpose of this paper is to answer to following research questions: ${\bullet}$ What determinants are important to CI quality? ${\bullet}$ What is the relationship between CI quality factors and the usefulness of web-enabled CI? ${\bullet}$ Does CI type have a moderating effect on the relationship between CI quality, its determinants, and CI usefulness? Online survey using Google Docs with email and Kakao Talk was conducted for collecting data from Wikipedia and Naver KnowledgeiN users. A totoal of 490 valid responses were collected, where users of Wikipedia were 220 while users of Naver KnowledgeiN were 270. Expertise of contributors, community size, and diversity of contributors were identified as core determinants of perceived CI quality. Perceived CI quality has significantly influenced perceived CI usefulness from a user's perspective. For improving CI quality, it is believed that organizations should ensure proper crowd size, facilitate CI contributors' diversity and attract as many expert contributors as possible. Hypotheses that CI type plays a role of moderator were partially supported. First, the relationship between expertise of contributors and perceived CI quality was different according to CI type. The expertise of contributors played a more important role in CI quality in the case of Q&A services such as Knowledge iN compared to wiki services such as Wikipedia. This implies that Q&A service requires more expertise and experiences in particular areas rather than the case of Wiki service to improve service quality. Second, the relationship between community size and perceived CI quality was different according to CI type. The community size has a greater effect on CI quality in case of Wiki service than that of Q&A service. The number of contributors in Wikipeda is important because Wiki is an encyclopedia service which is edited and revised repeatedly from many contributors while the answer given in Naver Knowledge iN can not be corrected by others. Finally, CI quality has a greater effect on its usefulness in case of Wiki service rather than Q&A service. In this paper, we suggested implications for practitioners and theorists. Organizations offering services based on collective intelligence try to improve expertise of contributeros, to increase the number of contributors, and to facilitate participation of various contributors.

• Economic and Environmental Geology
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• v.54 no.2
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• pp.233-245
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• 2021

Many studies on the microstructures in rocks have been conducted using experimental methods with various equipment as well as natural rock studies to see the development of microstructures and understand their mechanisms. Grain boundary migration of mineral aggregates in rocks could cause grain growth or grain size changes during metamorphism or deformation as one of the main recrystallization mechanisms. This study suggests improved ways regarding the analog material experiments with reformed equipment to see sequential observations of these grain boundary migration. It can be more efficient than the existing techniques and carry out an appropriate microstructure analysis. This reformed equipment was implemented to enable optical manipulation by mounting polarizing plates capable of rotating operation on a stereoscopic microscope and a deformation rig capable of experimenting with analog materials. The equipment can automatically control the temperature and strain rate of the deformation rig by microcontrollers and programming and can take digital photomicrographs with constant time intervals during the experiment to observe any microstructure changes. The composite images synthesized using images by rotated polarizing plates enable us to see more accurate grain boundaries. As a rock analog material, norcamphor(C7H10O) was used, which has similar birefringence to quartz. Static grain growth and simple shear deformation experiments were performed using the norcamphor to verify the effectiveness of the equipment. The static grain growth experiments showed the characteristics of typical grain growth behavior. The number of grains decreases and the average grain size increases over time. These case experiments also showed a clear difference between the growth curves with three temperature conditions. The result of the simple shear deformation experiment under the medium temperature-low strain rate showed no significant change in the average grain size but presented the increased elongation of grain shapes in the direction of about 53° regarding the direction perpendicular to the shearing direction as the shear strain increases over time. These microstructures are interpreted as both the plastic deformation and the internal recovery process in grains are balanced by the deformation under the given experimental conditions. These experiments using the reformed equipment represent the ability to sequentially observe changing the microstructure during experiments as desired in the tests with the analog material during the entire process.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.