• Title/Summary/Keyword: artificial categories

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Evaluation Standard for Performance of Artificial Intelligence Systems: ISO/IEC TR 24029-1 (인공지능 시스템의 성능 평가 표준: ISO/IEC TR 24029-1)

  • Seongsoo Lee
    • Journal of IKEEE
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    • v.27 no.3
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    • pp.350-354
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    • 2023
  • This paper describes ISO/IEC TR 24029-1, an international standard to evaluate the performance of artificial intelligence systems. ISO/IEC TR 24029-1 defines the performance measures of artificial intelligence systems in two categories, i.e. interpolation and classificiation. Performance measures in the interpolation categories mean how much the predicted values of the artificial intelligence system is close to the real values. Performance measures in the classification categories mean how much the predicted classes of the artificial intelligence system is equal to the real classes. Based on these performance measures, performance of artificial intelligence systems can be evaluated and performance of different artificial intelligence systems can be compared.

Analysis of Subject Category on Artificial Intelligence Discourse in Newspaper Articles (신문기사에 나타난 인공지능 담론에 대한 주제범주 분석)

  • Lee, Soo-Sang
    • Journal of Korean Library and Information Science Society
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    • v.48 no.4
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    • pp.21-47
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    • 2017
  • This study aims to analyze features of topics about AI(Artificial Intelligence) which is gaining a massive attention these days. Newspaper articles published from 2016 to June, 2017 were selected to analyze key subjects. The reason why the period was selected is people started to get attention on AI since 2016 as AlphaGo came out and gave a shock. The number of coded main message was 1,210 in 525 newspaper articles in total. The messages were categorized as three subject categories: the seven major categories, 62 middle categories. and minor categories. The seven major categories contains issues such as AI research, AI application, AI business, AI era, AI argument, AlphaGo, and other topics. The first features of issues about AI found in the major subject categories is that they are various and complicate. Second, it is important that social and policy-level issues related AI, such as job losses, misuse, and error should be dealt with to utilize AI safely. Last, issues related the role of human and revolution of education system in the AI era were shown as subjects which are important but hard to discuss.

The Semantic System in Late Korean-English Bilinguals (후기 한국어-영어 이중언어자의 의미체계)

  • Jeong, Woo-Rim;Kim, Min-Jung;Lee, Seung-Bok
    • Korean Journal of Cognitive Science
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    • v.19 no.2
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    • pp.177-203
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    • 2008
  • The present study was aimed to compare the semantic systems represented by the lexicon between L1 and L2 in late Korean-English bilinguals. The participants performed the word-picture matching task. the task was to decide whether the pictures represent the previously presented words' meaning. The words were the basic level categories. The stimuli were consisted of common object belonged to two different semantic categories (natural and artificial). To control the translation strategies, the SOA were manipulated as 650ms(Exp. 1) and 250ms(Exp. 2). No translation effort was found in the comparison of the two experiments. In both experiment, the RTs were faster in L1 rendition, and it took longer to decide the stimuli in natural categories than with artificial ones in L1. However, this category effect was not observed in L2. The results showed the differences in the organization of semantic representations in the brain through the bilinguals' two languages. While L1 semantic knowledge might be more systematically organized, that of L2 seems to be less well organized, at least by late bilinguals who participated in the present study.

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Artificial Intelligence in Personalized ICT Learning

  • Volodymyrivna, Krasheninnik Iryna;Vitaliiivna, Chorna Alona;Leonidovych, Koniukhov Serhii;Ibrahimova, Liudmyla;Iryna, Serdiuk
    • International Journal of Computer Science & Network Security
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    • v.22 no.2
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    • pp.159-166
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    • 2022
  • Artificial Intelligence has stimulated every aspect of today's life. Human thinking quality is trying to be involved through digital tools in all research areas of the modern era. The education industry is also leveraging artificial intelligence magical power. Uses of digital technologies in pedagogical paradigms are being observed from the last century. The widespread involvement of artificial intelligence starts reshaping the educational landscape. Adaptive learning is an emerging pedagogical technique that uses computer-based algorithms, tools, and technologies for the learning process. These intelligent practices help at each learning curve stage, from content development to student's exam evaluation. The quality of information technology students and professionals training has also improved drastically with the involvement of artificial intelligence systems. In this paper, we will investigate adopted digital methods in the education sector so far. We will focus on intelligent techniques adopted for information technology students and professionals. Our literature review works on our proposed framework that entails four categories. These categories are communication between teacher and student, improved content design for computing course, evaluation of student's performance and intelligent agent. Our research will present the role of artificial intelligence in reshaping the educational process.

Intelligent Resource Management Schemes for Systems, Services, and Applications of Cloud Computing Based on Artificial Intelligence

  • Lim, JongBeom;Lee, DaeWon;Chung, Kwang-Sik;Yu, HeonChang
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1192-1200
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    • 2019
  • Recently, artificial intelligence techniques have been widely used in the computer science field, such as the Internet of Things, big data, cloud computing, and mobile computing. In particular, resource management is of utmost importance for maintaining the quality of services, service-level agreements, and the availability of the system. In this paper, we review and analyze various ways to meet the requirements of cloud resource management based on artificial intelligence. We divide cloud resource management techniques based on artificial intelligence into three categories: fog computing systems, edge-cloud systems, and intelligent cloud computing systems. The aim of the paper is to propose an intelligent resource management scheme that manages mobile resources by monitoring devices' statuses and predicting their future stability based on one of the artificial intelligence techniques. We explore how our proposed resource management scheme can be extended to various cloud-based systems.

Implementation and Verification of Multi-level Convolutional Neural Network Algorithm for Identifying Unauthorized Image Files in the Military (국방분야 비인가 이미지 파일 탐지를 위한 다중 레벨 컨볼루션 신경망 알고리즘의 구현 및 검증)

  • Kim, Youngsoo
    • Journal of Korea Multimedia Society
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    • v.21 no.8
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    • pp.858-863
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    • 2018
  • In this paper, we propose and implement a multi-level convolutional neural network (CNN) algorithm to identify the sexually explicit and lewdness of various image files, and verify its effectiveness by using unauthorized image files generated in the actual military. The proposed algorithm increases the accuracy by applying the convolutional artificial neural network step by step to minimize classification error between similar categories. Experimental data have categorized 20,005 images in the real field into 6 authorization categories and 11 non-authorization categories. Experimental results show that the overall detection rate is 99.51% for the image files. In particular, the excellence of the proposed algorithm is verified through reducing the identification error rate between similar categories by 64.87% compared with the general CNN algorithm.

A basic study on the development of alternative bait for octopus pots (문어 통발용 대체 미끼 개발을 위한 기초연구)

  • AN, Young-il
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.56 no.3
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    • pp.202-212
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    • 2020
  • In order to replace sardine baits for octopus pot, an efficacy experiment to lure with alternative bait (fermented skate or chicken skin in artificial crab or northern clam) pots and sardine pot were conducted in a circular water tank. The soaking time of the sardine bait was divided into two categories: six days or less and seven days or more. The behavioral response of octopus to the artificial bait pots and sardine pot were investigated. In the comparison of the luring effects between pots with fermented skate inside artificial crab or northern clam and sardine pot, the pot with artificial crab + fermented skate had better results than the other pots in the section distribution (31.6%) and the number of times the pot was entered into (20.0%) (p > 0.05). In the comparison of the luring effects between pots with chicken skin inside artificial crab or northern clam and sardine pot, the pot with northern clam + chicken skin had better results than the other pots in the section distribution (22.6%) and number of times the pot was entered into (55.6%) (p < 0.05). The results were also better compared to those of pot with artificial crab + fermented skate. From these results, it seems that in the luring effect aspect, sardine bait can be replaced with artificial bait consisting of chicken skin inside northern clam.

Exploring Data Categories and Algorithm Types for Elementary AI Education (초등 인공지능 교육을 위한 데이터 범주와 알고리즘 종류 탐색)

  • Shim, Jaekwoun
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.167-173
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    • 2021
  • The purpose of this study is to discuss the types of algorithms and data categories in AI education for elementary school students. The study surveyed 11 pre-elementary teachers after providing education and practice on various data, artificial intelligence algorithm, and AI education platform for 15 weeks. The categories of data and algorithms considering the elementary school level, and educational tools were presented, and their suitability was analyzed. Through the questionnaire, it was concluded that it is most suitable for the teacher to select and preprocess data in advance according to the purpose of the class, and the classification and prediction algorithms are suitable for elementary AI education. In addition, it was confirmed that Entry is most suitable as an AI educational tool, and materials that explain mathematical knowledge are needed to educate the concept of learning of AI. This study is meaningful in that it specifically presents the categories of algorithms and data with in AI education for elementary school students, and analyzes the need for related mathematics education and appropriate AI educational tools.

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University Students' Thoughts on Artifical Abortion

  • Kim, Jungae
    • International Journal of Advanced Culture Technology
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    • v.10 no.2
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    • pp.122-129
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    • 2022
  • This study is a phenomenological qualitative study that confirms the structure of college students' thoughts on artificial abortion. The data collection period was from 5 March to 10 April 2022. To this end, a total of three interviews were conducted on seven college students aged 20 to 25. Interview data were conducted through analysis and interpretation using the phenomenological research method, the Giorgi method, and as a result, 40 semantic units were derived, grouped into six sub-components, and divided into three categories. As a result of the analysis, college students' thoughts on artificial abortion consisted of fetal rights, respect for women's rights, and choices for a healthy life. Based on the above meaning, college students' thoughts on artificial abortion were, in conclusion, that considering the happiness of the baby and the quality of life of the woman, consideration for non-marriage mothers was more urgent than legal sanctions, and that abortion was not irresponsible. Accordingly, this study suggests that understanding and consideration for pregnant women should be prioritized over legal sanctions.

Design of Artificial Intelligence Course for Humanities and Social Sciences Majors

  • KyungHee Lee
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.4
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    • pp.187-195
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    • 2023
  • This study propose to develop artificial intelligence liberal arts courses for college students in the humanities and social sciences majors using the entry artificial intelligence model. A group of experts in computer, artificial intelligence, and pedagogy was formed, and the final artificial intelligence liberal arts course was developed using previous research analysis and Delphi techniques. As a result of the study, the educational topics were largely composed of four categories: image classification, image recognition, text classification, and sound classification. The training consisted of 1) Understanding the principles of artificial intelligence, 2) Practice using the entry artificial intelligence model, 3) Identifying the Ethical Impact, and 4) Based on learned, team idea meeting to solve real-life problems. Through this course, understanding the principles of the core technology of artificial intelligence can be directly implemented through the entry artificial intelligence model, and furthermore, based on the experience of solving various real-life problems with artificial intelligence, and it can be expected to contribute positively to understanding technology, exploring the ethics needed in the artificial intelligence era.