• Title/Summary/Keyword: Proof learning

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Adaptive Learning Control of Neural Network Using Real-Time Evolutionary Algorithm (실시간 진화 알고리듬을 통한 신경망의 적응 학습제어)

  • Chang, Sung-Ouk;Lee, Jin-Kul
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.6
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    • pp.1092-1098
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    • 2002
  • This paper discusses the composition of the theory of reinforcement teaming, which is applied in real-time teaming, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line teaming method. The individuals are reduced in order to team the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It is possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because of the teaming process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

Overcoming framing-difference between teacher and students - an analysis of argumentation in mathematics classroom - (틀의 차이를 극복하기 - 수학교실에서의 논증분석 연구 -)

  • Kim, Dong-Won
    • The Mathematical Education
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    • v.46 no.2 s.117
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    • pp.173-192
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    • 2007
  • We define mathematical learning as a process of overcoming framing difference of teachers and students, two main subjects in a mathematics class. We have reached this definition to the effect that we can grasp a mathematical classroom per so and understand students' mathematical learning in the context. We could clearly understand the process in which the framing differences are overcome by analyzing mutual negotiation of informants in specific cultural models, both in its form as well as in its meaning. We review both of the direct and indirect forms of negotiation while keeping track of 'evolution of subject' in terms of content of negotiation. More specifically, we discuss direct negotiation briefly and review indirect negotiation from three distinct themes of (1) argument structure, (2) revoicing, and (3) development patterns and narrative structure of proof. In addition, we describe the content of negotiation under the title of 'Evolution of Subject.' We found that major modes of mutual negotiation are inter-reference and appropriation while the product of continued negotiation is inter-resemblance.

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Generation of Super-Resolution Benchmark Dataset for Compact Advanced Satellite 500 Imagery and Proof of Concept Results

  • Yonghyun Kim;Jisang Park;Daesub Yoon
    • Korean Journal of Remote Sensing
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    • v.39 no.4
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    • pp.459-466
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    • 2023
  • In the last decade, artificial intelligence's dramatic advancement with the development of various deep learning techniques has significantly contributed to remote sensing fields and satellite image applications. Among many prominent areas, super-resolution research has seen substantial growth with the release of several benchmark datasets and the rise of generative adversarial network-based studies. However, most previously published remote sensing benchmark datasets represent spatial resolution within approximately 10 meters, imposing limitations when directly applying for super-resolution of small objects with cm unit spatial resolution. Furthermore, if the dataset lacks a global spatial distribution and is specialized in particular land covers, the consequent lack of feature diversity can directly impact the quantitative performance and prevent the formation of robust foundation models. To overcome these issues, this paper proposes a method to generate benchmark datasets by simulating the modulation transfer functions of the sensor. The proposed approach leverages the simulation method with a solid theoretical foundation, notably recognized in image fusion. Additionally, the generated benchmark dataset is applied to state-of-the-art super-resolution base models for quantitative and visual analysis and discusses the shortcomings of the existing datasets. Through these efforts, we anticipate that the proposed benchmark dataset will facilitate various super-resolution research shortly in Korea.

A Mathematics Tutoring Model That Supports Interactive Learning of Problem Solving Based on Domain Principles (공식원리에 기반한 대화식 문제해결 학습을 지원하는 수학교수 모형)

  • Kook, Hyung-Joon
    • The KIPS Transactions:PartB
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    • v.8B no.5
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    • pp.429-440
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    • 2001
  • To achieve a computer tutor framework with high learning effects as well as practicality, the goal of this research has been set to developing an intelligent tutor for problem-solving in mathematics domain. The maine feature of the CyberTutor, a computer tutor developed in this research, is the facilitation of a learning environment interacting in accordance with the learners differing inferential capabilities and needs. The pedagogical information, the driving force of such an interactive learning, comprises of tutoring strategies used commonly in various domains such as phvsics and mathematics, in which the main contents of learning is the comprehension and the application of principles. These tutoring strategies are those of testing learners hypotheses test, providing hints, and generating explanations. We illustrate the feasibility and the behavior of our propose framework with a sample problem-solving learning in geometry. The proposed tutorial framework is an advancement from previous works in several aspects. Firstly, it is more practical since it supports handing of a wide range of problem types, including not only proof types but also finding-unkown tpes. Secondly, it is aimed at facilitating a personal tutor environment by adapting to learners of varying capabilities. Finally, learning effects are maximized by its tutorial dialogues which are derived from real-time problem-solving inference instead of from built-in procedures.

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A Case Study on Students' Concept Images of the Uniform Convergence of Sequences of Continuous Functions

  • Jeong, Moonja;Kim, Seong-A
    • Research in Mathematical Education
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    • v.17 no.2
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    • pp.133-152
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    • 2013
  • In this research, we investigated students' understanding of the definitions of sequence of continuous functions and its uniform convergence. We selected three female and three male students out of the senior class of a university and conducted questionnaire surveys 4 times. We examined students' concept images of sequence of continuous functions and its uniform convergence and also how they approach to the right concept definitions for those through several progressive questions. Furthermore, we presented some suggestions for effective teaching-learning for the sequences of continuous functions.

Teaching Diverse Proofs of Means and Inequalities and Its Implications (여러 가지 평균과 부등식을 이용한 대학수학 학습)

  • Kim, Byung-Moo
    • Communications of Mathematical Education
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    • v.19 no.4 s.24
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    • pp.699-713
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    • 2005
  • In this paper, we attempted to find out the meaning of several means and inequalities, their relationships and proposed the effective ways to teach them in college mathematics classes. That is, we introduced 8 proofs of arithmetic-geometric mean equality to explain the fact that there exist diverse ways of proof. The students learned the diverseproof-methods and applied them to other theorems and projects. From this, we found out that the attempt to develop the students' logical thinking ability by encouraging them to find out diverse solutions of a problem could be a very effective education method in college mathematics classes.

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Intelligent Control of Induction Motor Using Hybrid System GA-PSO

  • Kim, Dong-Hwa;Park, Jin-Il
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1086-1091
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    • 2005
  • This paper focuses on intelligent control of induction motor by hybrid system consisting of GA-PSO. Induction motor has been using in industrial area. However, it is challengeable on how we control effectively. From this point, an optimal solution using GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) is introduced to intelligent control. In this case, it is possible to obtain local solution because chromosomes or individuals which have only a close affinity can convergent. To improve an optimal learning solution of control, This paper deal with applying PSO and Euclidian data distance to mutation procedure on GA's differentiation. Through this approaches, we can have global and local optimal solution together, and the faster and the exact optimal solution without any local solution. Four test functions are used for proof of this suggested algorithm.

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A Re-Examination of the Area formula of triangles as an invariant of Euclidean geometry (유클리드 기하의 고유한 성질로서의 삼각형 넓이 공식에 대한 재음미)

  • Choi Young-Gi;Hong Gap-Ju
    • The Mathematical Education
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    • v.45 no.3 s.114
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    • pp.367-373
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    • 2006
  • This study suggests that it is necessary to prove that the values of three areas of a triangle, which are obtained by the multiplication of the respective base and its corresponding height, are the same. It also seeks to deeply understand the meaning of Area formula of triangles by exploring some questions raised in the analysis of the proof. Area formula of triangles expresses the invariance of congruence and additivity on one hand, and the uniqueness of parallel line, one of the characteristics of Euclidean geometry, on the other. This discussion can be applied to introducing and developing exploratory learning on area in that it revisits the ordinary thinking on area.

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A Study on the M2M Energy Trading System Using Proof of Location Blockchain Network (위치증명기반 블록체인 네트워크를 활용한 사물 간 에너지 직거래 시스템에 관한 연구)

  • Kim, Young-Gon;Heo, Keol;Choi, Jung-In
    • Journal of Energy Engineering
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    • v.29 no.3
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    • pp.86-90
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    • 2020
  • This paper examines a blockchain network-based transaction system using location proofing in power direct transactions between networked energy clouds, energy communities, and prosumer machines participating in smart cities. It utilizes location-based blockchain network technology, which enables long-distance travel with recharging by power purchases during autonomous movements, autonomous electric vehicles that can purchase and sell electricity, and solar street lights that can be produced and sold in fixed form. In addition, it is possible to provide optimum power transaction matching and settlement reliability between machines without human intervention in power transactions between electric chargers. It also introduces a business-to-object business model between autonomous machines that exist in multiple and different spaces and through energy clouds that are expected to be scattered with various transaction prices, policies, and incentives.

Design of Machine Learning based Smart Service Abstraction Layer for Future Network Provisioning (미래 네트워크 제공을 위한 기계 학습 기반 스마트 서비스 추상화 계층 설계)

  • Vu, Duc Tiep;N., Gde Dharma;Kim, Kyungbaek;Choi, Deokjai
    • Proceedings of the Korea Information Processing Society Conference
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    • 2016.10a
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    • pp.114-116
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    • 2016
  • Recently, SDN and NFV technology have been developed actively and provide enormous flexibility of network provisioning. The future network services would generally involve many different types of services such as hologram games, social network live streaming videos and cloud-computing services, which have dynamic service requirements. To provision networks for future services dynamically and efficiently, SDN/NFV orchestrators must clearly understand the service requirements. Currently, network provisioning relies heavily on QoS parameters such as bandwidth, delay, jitter and throughput, and those parameters are necessary to describe the network requirements of a service. However it is often difficult for users to understand and use them proficiently. Therefore, in order to maintain interoperability and homogeneity, it is required to have a service abstraction layer between users and orchestrators. The service abstraction layer analyzes ambiguous user's requirements for the desired services, and this layer generates corresponding refined services requirements. In this paper, we present our initial effort to design a Smart Service Abstraction Layer (SmSAL) for future network architecture, which takes advantage of machine learning method to analyze ambiguous and abstracted user-friendly input parameters and generate corresponding network parameters of the desired service for better network provisioning. As an initial proof-of-concept implementation for providing viability of the proposed idea, we implemented SmSAL with a decision tree model created by learning process with previous service requests in order to generate network parameters related to various audio and video services, and showed that the parameters are generated successfully.