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A Study on Game Mechanics and Dynamics of Survival Game Content (생존 게임 콘텐츠의 게임 메커닉·다이내믹 연구)

  • Kang, Jihye;Jang, Ahyoung;Song, Inhee
    • Journal of Korea Game Society
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    • v.18 no.4
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    • pp.5-14
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    • 2018
  • Nowadays, game development of new genres continues through convergence among existing genres, and the games of this hybrid-genre are gaining popularity around the world. Following this trend, it is meaningful to analyze the characteristic contents of the existing genre for more effective genre fusion. In this paper, in the genre of survival game, a genre of digital game, we would like to select a representative survival game for analysis of survival content, which is a key goal and core of the game, to identify common and differentiated features. For this purpose, we have studied game mechanics and game dynamic components around the contents of the survival game, based on the MDA framework.

A Study on Algebraic Knowledge of Mathematics Teachers on Solving Polynomials and Searching Possibility of Self Learning the Knowledge (다항식의 해법에 대한 수학교사의 대수 내용지식과 자립연수 가능성 탐색)

  • Shin, Hyunyong;Han, Inki
    • Communications of Mathematical Education
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    • v.29 no.4
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    • pp.661-685
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    • 2015
  • This study is to search for a program of professional development of mathematics teachers on the viewpoint of content knowledge of mathematics. To do this, we select algebraic subject as content knowledge for solution of polynomials and develop material for group study based on selected subject. We supply the developed material to teachers and discuss the possibility of application and the acceptability of it. For discussion, we collect data through tests and questionnaire. Through analysing the data, we obtain the positive result.

Investigations into the Causes of Wardrobe Pveferene/Dispreference through Open-ended Response Questionnaire (자유 기술 응답을 통한 보유 의복 선호/비선호 원인 구조 고찰)

  • Kim Saehee
    • Journal of the Korean Society of Costume
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    • v.54 no.8
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    • pp.59-74
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    • 2004
  • The Purposes of this study are to investigate consumers' causes of clothing preference and dispreference separately, and to get 'real' descriptions about that causes using an open-ended response questionnaire. The sample was composed of 81 undergraduate students. Subjects were asked to select their preferred clothing and disprefered clothing respectively among wardrobes they have and to describe the causes of that preference/dispreference. The data was collected through an open-ended response questionnaire and analyzed using content analysis. The system for content analysis was divided into the view Point of image, clothing itself, wearer's physical characteristics, wearing situation, others' response, wearer's values, wearer's consciousness, and purchase process. Image was the primary cause that raised clothing preference, and clothing itself, wearer's physical characteristic, wearing situation, others' response, wearer's consciousness, wearer's values, and purchase process followed. In audition. wearer's physical characteristic was the primary cause that raised clothing dispreference. and image, clothing itself. wearer's consciousness, wearer's values. wearing situation, purchase process, and others' response followed. Finally, the framework for the causes of clothing preference/dispreference was developed.

Adaptive Feature Selef-selection and Multiple SOFM Neural network for Content-based image Retrieval System (내용기반 복합 영상 검색 시스템을 위한 적응적 특징 자가선택과 다중 SOFM 신경망)

  • 임승린
    • Journal of the Korea Society of Computer and Information
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    • v.5 no.2
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    • pp.22-29
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    • 2000
  • The purpose of this paper is to propose a method to maximize a content-based image retrieval efficiency in multiple images. To perform an image retrieval job efficiently, it is necessary to minimize the number of candidate-images. Furthermore, a miximum efficiency of image retrieval could not be expected if an image retrieval job in the multiple images is done on the basis of patterns of single image distinctive features. In this method, a multiple SOFM neural network system is adopted to select automatically distinctive feature patterns which have a maximum efficiency of image retrieval in the multiple images. In this method. an image retrieval efficiency is improved 3% than individual features and the number of candidate-images is reduced by the multiple SOFM neural network system.

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Awareness and Use of Cloud Computing Services and Technologies by Librarians in Selected Universities in Edo State

  • Aiyebelehin, Afebuameh James;Makinde, Bosede;Odiachi, Rosemary;Mbakwe, Cynthia Chiamaka
    • International Journal of Knowledge Content Development & Technology
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    • v.10 no.3
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    • pp.7-20
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    • 2020
  • This study examined the awareness and use of cloud computing services by librarians in selected universities in Edo State. A descriptive survey research design was employed and the instrument used was questionnaire. The population of the study was 132 professional and Para-professional librarians. The total enumeration technique was used to select the entire population because the size was manageable. Simple percentage, frequency count, and mean were used to analyze the data collected. From the analysis of data gathered, it was found that the librarians are aware of the use of OCLC, world cat, and Google docs to a very high extent. It was found that the librarians used cloud computing services and technologies for collection development functions and cataloging. Based on the findings it was recommended that management of the libraries should support librarians by providing adequate funding to the library in order to support the acquisition and maintenance of infrastructure for cloud computing.

Studies on the Application of Byproduct Composts as Substitute for Yacto in Yang-jik Nursery of Ginseng (인삼 양직모밭 약토대체 부산물퇴비 시용 연구)

  • Kang, Seung-Weon;Yeon, Byeong-Yeol;Lee, Sung-Woo;Hyun, Dong-Yun;Bae, Yeoung-Seuk;Hyeon, Geun-Soo
    • Korean Journal of Medicinal Crop Science
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    • v.17 no.6
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    • pp.415-420
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    • 2009
  • This study was carried out to select economical byproduct composts as the substitute for the traditional organic fertilizer, Yacto, in the cultivation of ginseng seedlings, and to investigate the application method of a selected compost. Among tested byproduct composts, popped rice hull compost was the best substitute for Yacto, while the application of domestic animal manure composts resulted in red skinned roots of ginseng seedlings. Optimal mixing ratio of the popped rice hull compost with virgin soil (fine sand) were 3~4 : 1 in bulk, showing the same root yield compared to that of conventional seedbed soil. When the popped rice hull compost was lower than $1\;{\pm}\;0.1%$ in nitrogen content, the expeller cake of oil seed was added to seedbed soil to rise nitrogen content until $1\;{\pm}\;0.1%$.

LMS for Web based e-Learning on the SCORM

  • Woo, Young-Hwan;Chung, Jin-Wook;Kim, Seok-Soo;Kim, Soon-Gohn
    • Journal of information and communication convergence engineering
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    • v.2 no.2
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    • pp.80-83
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    • 2004
  • The core purpose of the system proposed in this paper is to help learners pursue proactive and self-oriented education by allowing learners to proactively configure their own content, that is, learners no longer have to be restricted by prescribed sequence of lectures. Although a variety of standardization and Learning Management System (LMS) were produced to develop and effectively manage web contents in response to active diffusion of internet application, practical changes to assist online learners are not yet to be found. In this paper, I would like to introduce a LMS that can support self-leading education by providing various types of learners at Virtual University with delicately organized educational contents for maximum efficiency. The system allows a learner to select a lecture or a chapter which has been presorted to meet his educational needs and intellectual ability. In general, most LMSs cannot meet every individual's educational needs because they structure their programs by letting learners simply choose from a list of available lectures at prescribed level or difficulty. However the Self-Leading LMS eliminates such boundaries by allowing learners to choose contents and difficulty within the limit set by their own educational competence.

An Evaluative Analysis of 'U-KNOU Campus' System and its Mobile Platform

  • Seol, Jinah
    • Journal of Internet Computing and Services
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    • v.20 no.5
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    • pp.79-86
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    • 2019
  • This paper is an overview of key elements of Korea National Open University's smart mobile learning system, and an attempt to evaluate its main services relative to the FRAME model and the Mobile Learning Development Model for distance learning in higher education. KNOU improved its system architecture to one based on xMOOC e-learning content delivery while also upgrading its PC-based online/mobile learning services to facilitate an easier and more convenient access to lectures and for better interactivity. From the users' viewpoint, the upgraded 'U-KNOU Campus' allows for a more integrated search capability coupled with better course recommendations and a customized notification service. Using the new system, the students can access not only the school- and peer-issued messages via online bulletin boards but also share information and pose questions to others including to the school faculty/officials and system administrators. Additionally, a new mobile payment method has been incorporated into the system so that the students can select and pay for additional courses from anywhere. In spite of these advances, the issue of device usability and content development remain; specifically U-KNOU Campus needs to improve its instructor-learner and learner-to-learner interactivity and mobile evaluation interface.

An Efficient Machine Learning-based Text Summarization in the Malayalam Language

  • P Haroon, Rosna;Gafur M, Abdul;Nisha U, Barakkath
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.6
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    • pp.1778-1799
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    • 2022
  • Automatic text summarization is a procedure that packs enormous content into a more limited book that incorporates significant data. Malayalam is one of the toughest languages utilized in certain areas of India, most normally in Kerala and in Lakshadweep. Natural language processing in the Malayalam language is relatively low due to the complexity of the language as well as the scarcity of available resources. In this paper, a way is proposed to deal with the text summarization process in Malayalam documents by training a model based on the Support Vector Machine classification algorithm. Different features of the text are taken into account for training the machine so that the system can output the most important data from the input text. The classifier can classify the most important, important, average, and least significant sentences into separate classes and based on this, the machine will be able to create a summary of the input document. The user can select a compression ratio so that the system will output that much fraction of the summary. The model performance is measured by using different genres of Malayalam documents as well as documents from the same domain. The model is evaluated by considering content evaluation measures precision, recall, F score, and relative utility. Obtained precision and recall value shows that the model is trustable and found to be more relevant compared to the other summarizers.

Recommendation of tourist attractions based on Preferences using big data

  • KIM HYUN SEOK;Gi-hwan Ryu;kim im yeo-reum
    • International Journal of Advanced Culture Technology
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    • v.11 no.3
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    • pp.327-331
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    • 2023
  • This paper proposes a tourist destination recommendation application that combines a chatbot and a recommendation system. The data to be entered into the chatbot was through big data on social media. Through TEXTOM, a total of 22,701 data were collected over a one-year period from January 2022 to January 2023. Non-terms that interfere with analysis were removed through the data purification process. Using refined data, network visualization and CONCOR analysis were used to identify the information users want to obtain about travel to Jeju Island, and categories for each cluster were organized. The content was intuitively organized so that even those who approached it for the first time could easily use it, reducing the difficulty of operating the application. In this paper, users can select their own preferences and receive information. In addition, a tool called a chatbot allows users to focus more on the process of acquiring information by gaining a sense of reality while operating the application. This suggests an application that can reach the purpose of the curator by affecting the user's desire to visit tourist attractions.