• Title/Summary/Keyword: 인공지능을 위한 수학

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Analysis of privacy issues and countermeasures in neural network learning (신경망 학습에서 프라이버시 이슈 및 대응방법 분석)

  • Hong, Eun-Ju;Lee, Su-Jin;Hong, Do-won;Seo, Chang-Ho
    • Journal of Digital Convergence
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    • v.17 no.7
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    • pp.285-292
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    • 2019
  • With the popularization of PC, SNS and IoT, a lot of data is generated and the amount is increasing exponentially. Artificial neural network learning is a topic that attracts attention in many fields in recent years by using huge amounts of data. Artificial neural network learning has shown tremendous potential in speech recognition and image recognition, and is widely applied to a variety of complex areas such as medical diagnosis, artificial intelligence games, and face recognition. The results of artificial neural networks are accurate enough to surpass real human beings. Despite these many advantages, privacy problems still exist in artificial neural network learning. Learning data for artificial neural network learning includes various information including personal sensitive information, so that privacy can be exposed due to malicious attackers. There is a privacy risk that occurs when an attacker interferes with learning and degrades learning or attacks a model that has completed learning. In this paper, we analyze the attack method of the recently proposed neural network model and its privacy protection method.

Designing Reward Function for Cooperative Traffic Signal Control at Multi-intersection (다중 교차로에서 협동적 신호제어를 위한 보상함수 설계)

  • Bae, Yo-han;Jang, Jin-heon;Song, Moon-hyuk
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.110-113
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    • 2022
  • Nowadays, breaking through the conventional traffic signal control method based on mathematical optimization, artificial intelligence began to be used in the area. In response to this trend, many studies are ongoing to figure out how to utilize AI technology properly for traffic signal optimization. They just simply focus on which method will work well besides lots of machine learning techniques and abandon the reward function engineering. In many cases, the reward function consists of the average delay of the vehicles in the intersection. However, this may lead to AI's misunderstanding about the traffic signal control: what AI regards as a good situation may not be realistic. Even the reward function itself may not meet the service level. Therefore, this study analyzes the problems of previous reward functions and will suggest how to reward function can be enhanced.

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Study on the Mathematics Teaching and Learning Artificial Intelligence Platform Analysis (수학 교수·학습을 위한 인공지능 플랫폼 분석 연구)

  • Park, Hye Yeon;Son, Bok Eun;Ko, Ho Kyoung
    • Communications of Mathematical Education
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    • v.36 no.1
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    • pp.1-21
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    • 2022
  • The purpose of this study is to analyze the current situation of EduTech, which is proposed as a way to build a flexible learning environment regardless of time and place according to the use of digital technology in mathematics subjects. The process of designing classes to use the EduTech platform, which is still in the development introduction stage, in public education is still difficult, and research to observe its effects and characteristics is also in its early stages. However, in the stage of preparing for future education, it is a meaningful process to grasp the current situation and point out the direction in preparation for the future in which EduTech will be actively applied to education. Accordingly, the current situation and utilization trends of EduTech at home and abroad were confirmed, and the functions and roles of EduTech platforms used in mathematics were analyzed. As a result of the analysis, the EduTech platform was pursuing learners' self-directed learning by constructing its functions so that they could be useful for individual learning of learners in hierarchical mathematics education. In addition, we have confirmed that the platform is evolving to be useful for teachers' work reduction, suitable activities, and evaluations learning management. Therefore, it is necessary to implement instructional design and individual customized learning support measures for students that can efficiently utilize these platforms in the future.

AI-Based Educational Platform Analysis Supporting Personalized Mathematics Learning (개별화 맞춤형 수학 학습을 지원하는 AI 기반 플랫폼 분석)

  • Kim, Seyoung;Cho, Mi Kyung
    • Communications of Mathematical Education
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    • v.36 no.3
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    • pp.417-438
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    • 2022
  • The purpose of this study is to suggest implications for mathematics teaching and learning when using AI-based educational platforms that support personalized mathematics learning. To this end, we selected five platforms(Knock-knock! Math Expedition, knowre, Khan Academy, MATHia, CENTURY) and analyzed how the AI-based educational platforms for mathematics reflect the three elements(PLP, PLN, PLE) to support personalized learning. The results of this study showed that although the characteristics of PLP, PLN, and PLE implemented on each platform varied, they were designed to form PLEs that allow learners to make their autonomous decisions about learning based on PLP and PLN. The significance of this study can be found in that it has improved the understanding and practicability of personalized mathematics learning with the AI-based educational platforms.

혼돈이론과 농업에의 응용

  • 조성인
    • Journal of Bio-Environment Control
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    • v.4 no.2
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    • pp.246-252
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    • 1995
  • 작물, 가축, 농산물을 학문의 대상으로 하는 농학은 기상, 토양 등과 같은 자연 현상으로부터 필요한 데이터를 획득하여 이용한다. 그러나, 이들 데이터는 많은 환경 요인의 영향을 받아 그 거동이 매우 복잡한 비선형적 현상을 나타내는 것이 대부분이다. 따라서, 실험을 통해 획득된 데이터의 처리 및 모형화 등을 위해 기존의 수학적, 통계적 방법을 이용하는 경우에 많은 어려움을 겪게 된다. 이에 최근에는 신경회로망 및 퍼지 이론 등과 같은 인공 지능 기법을 이용하여 이러한 문제점을 해결하기 위한 연구가 활발히 진행되고 있다. 본 강좌에서는 복잡한 비선형 특성 특히 임의적 거동을 보이는 자연 현상을 기술하기 위해 최근에 대두되고 있는 혼돈 이론에 대한 소개를 하고자 한다.(중략)

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A Study on Multiplexer Assignment Problem for Efficient Dronebot Network (효율적인 드론봇 네트워크 구성을 위한 Multiplexer 할당모형에 관한 연구)

  • Seungwon Baik
    • Journal of The Korean Institute of Defense Technology
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    • v.5 no.2
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    • pp.17-22
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    • 2023
  • In the midst of the development of science and technology based on the 4th industrial revolution, the ROK Army is moving forward with the ARMY TIGER 4.0 system, a ground combat system that combines future advanced science and technology. The system is developing around an AI-based hyper-connected ground combat system, and has mobility, intelligence, and networking as core concepts. Especially, the dronebot combat system is used as a compound word that refers to unmanned combat systems including drones and ground unmanned systems. In future battlefields, it is expected that the use of unmanned and artificial intelligence-based weapon systems will increase. During the transition to a complete unmanned system, it is a very important issue to ensure connectivity individual unmanned systems themselves or between manned and unmanned systems on the battlefield. This paper introduces the Multiplexer Allocation Problem (MAP) for effective command control and communication of UAV/UGV, and proposes a heuristic algorithm. In addition, the performance of the proposed algorithm is analyzed by comparing the solutions and computing time. Also, we discuss future research area for the MAP.

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A Case Study on the Effect of the Artificial Intelligence Storytelling(AI+ST) Learning Method (인공지능 스토리텔링(AI+ST) 학습 효과에 관한 사례연구)

  • Yeo, Hyeon Deok;Kang, Hye-Kyung
    • Journal of The Korean Association of Information Education
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    • v.24 no.5
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    • pp.495-509
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    • 2020
  • This study is a theoretical research to explore ways to effectively learn AI in the age of intelligent information driven by artificial intelligence (hereinafter referred to as AI). The emphasis is on presenting a teaching method to make AI education accessible not only to students majoring in mathematics, statistics, or computer science, but also to other majors such as humanities and social sciences and the general public. Given the need for 'Explainable AI(XAI: eXplainable AI)' and 'the importance of storytelling for a sensible and intelligent machine(AI)' by Patrick Winston at the MIT AI Institute [33], we can find the significance of research on AI storytelling learning model. To this end, we discuss the possibility through a pilot study targeting general students of an university in Daegu. First, we introduce the AI storytelling(AI+ST) learning method[30], and review the educational goals, the system of contents, the learning methodology and the use of new AI tools in the method. Then, the results of the learners are compared and analyzed, focusing on research questions: 1) Can the AI+ST learning method complement algorithm-driven or developer-centered learning methods? 2) Whether the AI+ST learning method is effective for students and thus help them to develop their AI comprehension, interest and application skills.

Analysis of Recognition and Needs for Parents in Elementary, Middle, and High Schools for Mathematics Education (초·중등 학부모 대상 수학교과 인식 및 요구 조사)

  • Lee, Hyeung Ju;Kim, Hyeongsik;Ko, Ho Kyoung
    • Communications of Mathematical Education
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    • v.35 no.3
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    • pp.213-231
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    • 2021
  • This study is intended to investigate contents related to parents' perception and satisfaction level of school mathematics curriculum. Based on the results, this study intended to deduce implications for mathematics education in schools, child education, and parent education. According to the result of the survey, the more positively the parents perceived the value of the mathematics learning, the more positively the child perceived, and the higher the parent's participation rate in mathematics-related education was. In terms of perception of teaching and learning activities, it showed that the willingness to participate in educational programs was lower for the parents of middle and high school students than the parents of elementary school students and the parents of elementary school students also showed higher satisfaction level of school mathematics curriculum. parents have perceived the necessity of teaching and mathematics education to develop artificial intelligence or data analysis skills. It was also found that the parents of middle and high school students' participation experience in education had an effect on the satisfaction level of their children's math teacher's class preparedness. Parents perceived positively to how pragmatic mathematics curriculum can be and provided answers to what they wish in specific mathematics classes in learning methods and future mathematics learning. As this is for educational experts to consider much in-depth in the future, this study suggested the need for diverse parents' education related to mathematics including the expansion of mathematics education with parents' participation, the creation of a mathematics learning environment for future mathematics learning.

Future Tactical Communication System Development Plan (미래 전술통신체계의 발전 방안)

  • Kim, Junseob;Park, Sangjun;Cha, Jinho;Kim, Yongchul
    • Journal of Convergence for Information Technology
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    • v.11 no.6
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    • pp.14-23
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    • 2021
  • The Army is making efforts to increase combat power by incorporating technologies related to the Fourth Industrial Revolution into the field of defense. In order to utilize these technologies, it is necessary to develop a military tactical communication system that enables transmission and reception of data between command and control system and weapon systems. Therefore, in this paper, we analyze the tactical communication systems of the other countries, derive the limitations of the tactical communication system currently operating in the military. And, a multi-layered integrated operation structure centered on satellites and plans to provide communication on the move to small units are reviewed. Then, we present the necessity of a large-capacity transmission speed by predicting the amount of data that will be generated from weapon systems of the future, and a plan to efficiently manage the network using intelligent network technology.

Model Training and Data Augmentation Schemes For the High-level Machine Reading Comprehension (고차원 기계 독해를 위한 모델 훈련 및 데이터 증강 방안)

  • Lee, Jeongwoo;Moon, Hyeonseok;Park, Chanjun;Lim, Heuiseok
    • Annual Conference on Human and Language Technology
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    • 2021.10a
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    • pp.47-52
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    • 2021
  • 최근 지문을 바탕으로 답을 추론하는 연구들이 많이 이루어지고 있으며, 대표적으로 기계 독해 연구가 존재하고 관련 데이터 셋 또한 여러 가지가 공개되어 있다. 그러나 한국의 대학수학능력시험 국어 영역과 같은 복잡한 구조의 문제에 대한 고차원적인 문제 해결 능력을 요구하는 데이터 셋은 거의 존재하지 않는다. 이로 인해 고차원적인 독해 문제를 해결하기 위한 연구가 활발히 이루어지고 있지 않으며, 인공지능 모델의 독해 능력에 대한 성능 향상이 제한적이다. 기존의 입력 구조가 단조로운 독해 문제에 대한 모델로는 복잡한 구조의 독해 문제에 적용하기가 쉽지 않으며, 이를 해결하기 위해서는 새로운 모델 훈련 방법이 필요하다. 이에 복잡한 구조의 고차원적인 독해 문제에도 대응이 가능하도록 하는 모델 훈련 방법을 제안하고자 한다. 더불어 3가지의 데이터 증강 기법을 제안함으로써 고차원 독해 문제 데이터 셋의 부족 문제 또한 해소하고자 한다.

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