• Title/Summary/Keyword: Block Programming

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Design and implementation of an AI-based speed quiz content for social robots interacting with users (사람과 상호작용하는 소셜 로봇을 위한 인공지능 기반 스피드 퀴즈 콘텐츠의 설계와 구현)

  • Oh, Hyun-Jung;Kang, A-Reum;Kim, Do-Yun;Jeong, Gu-Min
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.13 no.6
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    • pp.611-618
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    • 2020
  • In this paper, we propose a design and implementation method of speed quiz content that can be driven by a social robot capable of interacting with humans, and a method of developing an intelligent module necessary for implementation. In addition, we propose a method of implementing speed quiz content through the process of constructing a map by arranging and connecting intelligent module blocks. Recently, software education has become mandatory and interest in programming is increasing. However, programming is difficult for students without basic knowledge of programming languages to directly access, and interest in block-type programming platforms suitable for beginners is growing. The block-type programming platform used in this paper is a platform that supports immediate and intuitive programming by supporting interactions between humans and robots. In this paper, the intelligent module implemented for the speed quiz content was used by blocking it within a block-type programming platform. In order to implement the scenario of the speed quiz content proposed in this paper, we implement a total of three image-based artificial intelligence modules. In addition to the intelligent module, various functional blocks were placed to implement the speed quiz content. In this paper, we propose a method of designing a speed quiz content scenario and a method of implementing an intelligent module for speed quiz content.

Development of Block-based Code Generation and Recommendation Model Using Natural Language Processing Model (자연어 처리 모델을 활용한 블록 코드 생성 및 추천 모델 개발)

  • Jeon, In-seong;Song, Ki-Sang
    • Journal of The Korean Association of Information Education
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    • v.26 no.3
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    • pp.197-207
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    • 2022
  • In this paper, we develop a machine learning based block code generation and recommendation model for the purpose of reducing cognitive load of learners during coding education that learns the learner's block that has been made in the block programming environment using natural processing model and fine-tuning and then generates and recommends the selectable blocks for the next step. To develop the model, the training dataset was produced by pre-processing 50 block codes that were on the popular block programming language web site 'Entry'. Also, after dividing the pre-processed blocks into training dataset, verification dataset and test dataset, we developed a model that generates block codes based on LSTM, Seq2Seq, and GPT-2 model. In the results of the performance evaluation of the developed model, GPT-2 showed a higher performance than the LSTM and Seq2Seq model in the BLEU and ROUGE scores which measure sentence similarity. The data results generated through the GPT-2 model, show that the performance was relatively similar in the BLEU and ROUGE scores except for the case where the number of blocks was 1 or 17.

Behavior Evolution of Autonomous Mobile Robot(AMR) using Genetic Programming Based on Evolvable Hardware

  • Sim, Kwee-Bo;Lee, Dong-Wook;Zhang, Byoung-Tak
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.2 no.1
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    • pp.20-25
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    • 2002
  • This paper presents a genetic programming based evolutionary strategy for on-line adaptive learnable evolvable hardware. Genetic programming can be useful control method for evolvable hardware for its unique tree structured chromosome. However it is difficult to represent tree structured chromosome on hardware, and it is difficult to use crossover operator on hardware. Therefore, genetic programming is not so popular as genetic algorithms in evolvable hardware community in spite of its possible strength. We propose a chromosome representation methods and a hardware implementation method that can be helpful to this situation. Our method uses context switchable identical block structure to implement genetic tree on evolvable hardware. We composed an evolutionary strategy for evolvable hardware by combining proposed method with other's striking research results. Proposed method is applied to the autonomous mobile robots cooperation problem to verify its usefulness.

Stereo-To-Multiview Conversion System Using FPGA and GPU Device (FPGA와 GPU를 이용한 스테레오/다시점 변환 시스템)

  • Shin, Hong-Chang;Lee, Jinwhan;Lee, Gwangsoon;Hur, Namho
    • Journal of Broadcast Engineering
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    • v.19 no.5
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    • pp.616-626
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    • 2014
  • In this paper, we introduce a real-time stereo-to-multiview conversion system using FPGA and GPU. The system is based on two different devices so that it consists of two major blocks. The first block is a disparity estimation block that is implemented on FPGA. In this block, each disparity map of stereoscopic video is estimated by DP(dynamic programming)-based stereo matching. And then the estimated disparity maps are refined by post-processing. The refined disparity map is transferred to the GPU device through USB 3.0 and PCI-express interfaces. Stereoscopic video is also transferred to the GPU device. These data are used to render arbitrary number of virtual views in next block. In the second block, disparity-based view interpolation is performed to generate virtual multi-view video. As a final step, all generated views have to be re-arranged into a single image at full resolution for presenting on the target autostereoscopic 3D display. All these steps of the second block are performed in parallel on the GPU device.

DeepBlock: Web-based Deep Learning Education Platform (딥블록: 웹 기반 딥러닝 교육용 플랫폼)

  • Cho, Jinsung;Kim, Geunmo;Go, Hyunmin;Kim, Sungmin;Kim, Jisub;Kim, Bongjae
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.3
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    • pp.43-50
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    • 2021
  • Recently, researches and projects of companies based on artificial intelligence have been actively carried out. Various services and systems are being grafted with artificial intelligence technology. They become more intelligent. Accordingly, interest in deep learning, one of the techniques of artificial intelligence, and people who want to learn it have increased. In order to learn deep learning, deep learning theory with a lot of knowledge such as computer programming and mathematics is required. That is a high barrier to entry to beginners. Therefore, in this study, we designed and implemented a web-based deep learning platform called DeepBlock, which enables beginners to implement basic models of deep learning such as DNN and CNN without considering programming and mathematics. The proposed DeepBlock can be used for the education of students or beginners interested in deep learning.

Improved Algorithm for Haplotype Block Partitioning : Application to Human Chromosome 21

  • Na, Kyoung-Rak;Kim, Sang-Jun;Kim, Sung-Kwon
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2003.10a
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    • pp.229-235
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    • 2003
  • Research of basis technology to construct the human haplotype map is one of active areas in SNP post-genomics research. Identification of haplotype block structure from haplotype data is key step in the haplotype map project. Several algorithms have been proposed for the block identification, including the greedy algorithm, and the dynamic programming based algorithm. This paper analyzed block partitioning method of several algorithm which has been proposed in recent years. HapBlock and HaploBlockFinder are programs used in our experiment.

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Designing Programming Curriculum for Developing Programming Pedagogical Content Knowledge of Pre-service Informatics Teachers (예비교사의 프로그래밍 교수내용지식 향상을 위한 프로그래밍 교육프로그램 설계)

  • An, Sangjin;Lee, Youngjun
    • The Journal of Korean Association of Computer Education
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    • v.19 no.2
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    • pp.1-10
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    • 2016
  • This study is for developing a programming education course to improve pre-service teachers' pedagogical content knowledge(PCK) of programming education. A 40-hour training course was designed with App Inventor, a block-based mobile programming environment, and with problem-based learning method and project-based learning method. After the curriculum was adopted to 12 undergraduate students, the effect of education was tested with a programming PCK questionnaire. As a result, after a 20-hour problem-based learning class, overall score and teaching method score were enhanced significantly. After another 20-hour project-based learning class, content knowledge, teaching method, and curriculum score were improved.

Operation and Satisfaction of Physical Computing Classes Using MODI (MODI를 활용한 피지컬 컴퓨팅 수업 운영 및 만족도)

  • Seo, Eunsil
    • Journal of Engineering Education Research
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    • v.26 no.1
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    • pp.37-44
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    • 2023
  • Recently, the Internet of Things is attracting attention as an important key technology of the 4th Industrial Revolution, and SW education using physical computing is suggested as a good alternative to supplement the problems raised by beginners in programming education. Among the many teaching tools that can be used for physical computing education, MODI is a modular manufacturing tool that anyone can easily assemble like Lego. MODI is a teaching tool that can improve learners' achievement by linking a self-linked block-type code editor called MODI Studio to lay the foundation for programming in a relatively small amount of time and immediately check the results in person. In this paper, a physical computing education method using MODI was designed to be applied to basic programming courses for programming beginners and applied to after-school classes for middle school students. As a result, it was found that students' interest and satisfaction were much higher in physical computing classes using MODI than in text-based programming classes. It can be seen that physical computing education that allows beginners to see and feel the results in person is more effective than grammar-oriented text programming, and it can have a positive effect on improving basic programming skills by increasing students' participation.

Large-scale Nonseparabel Convex Optimization:Smooth Case (대규모 비분리 콘벡스 최적화 - 미분가능한 경우)

  • 박구현;신용식
    • Journal of the Korean Operations Research and Management Science Society
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    • v.21 no.1
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    • pp.1-17
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    • 1996
  • There have been considerable researches for solving large-scale separable convex optimization ptoblems. In this paper we present a method for large-scale nonseparable smooth convex optimization problems with block-angular linear constraints. One of them is occurred in reconfiguration of the virtual path network which finds the routing path and assigns the bandwidth of the path for each traffic class in ATM (Asynchronous Transfer Mode) network [1]. The solution is approximated by solving a sequence of the block-angular structured separable quadratic programming problems. Bundle-based decomposition method [10, 11, 12]is applied to each large-scale separable quadratic programming problem. We implement the method and present some computational experiences.

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Exploring Ways to Learn Online Judge Problems in Block Programming Language (온라인 저지 문항을 블록 프로그래밍 언어로 학습하기 위한 방안 탐구)

  • HakNeung Go;Youngjun Lee
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.719-720
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    • 2023
  • 본 연구에서는 온라인 저지 문항을 블록 프로그래밍 언어로 학습하기 위한 방안에 대해서 탐구하였다. 온라인 저지를 활용한 프로그래밍 교육은 알고리즘을 설계하는 추상화 과정과 이를 프로그래밍 언어로 작성하는 자동화 과정이 포함되며 이는 컴퓨팅 사고력 발달에 영향을 준다. 온라인 저지는 대부분 텍스트 프로그래밍 언어(이하, TPL)에서 지원되어 초보 학습자가 사용하기에 어려움이 있다. 블록 프로그래밍 언어(이하, BPL)를 기반으로 한 온라인 저지는 BPL로 작성한 것을 TPL로 변환하는 방법과 그래픽 기반 문제상황을 해결하는 방법이 있으며 TPL로 변환하는 것은 텍스트 기반 온라인 저지 문항을 사용할 수 있으나 사용하는 방법이 어렵다. 반면 그래픽 기반 문제 상황은 사용하는 방법이 쉽지만 문항이 제한적이고 순차적 사고가 강조된다. 이에 엔트리 '스터디'와 '나의 학급-과제'를 이용하면 자동 평가 기능은 없지만 학습자가 익숙한 환경에서 학습할 수 있고 교사는 문항을 직접 개발할 수 있으며 문제 제시, 예시 작품 제시, 블록 제한, 과제제출 등을 사용하여 BPL에서 온라인 저지 문항을 학습할 수 있다.

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