• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.248-250
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• 1986

This paper explain application of expert system techniques from the latest theories of artificial intelligence to industrial process control. This controller continuously monitors a loop's response to disturbances and adapts the tuning parameters (P.I.D) to provide the best response to load upset or set-point change.

• Korean journal of aerospace and environmental medicine
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• v.29 no.2
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• pp.59-66
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• 2019

Artificial Intelligence (AI) born in 1956 is a general term that implies the use of a computer to make intelligent machines with minimal human intervention. AI is a topic dominating diverse discussions on the future of professional employment, change in the social standard and economic performance. In this paper, I describe fundamental concepts underlying AI and their significance to various fields including aviation and medicine. I highlight issues involved and describe the potential impacts and challenges to the industrial fields. While many benefits are expected in human life with AI integration, problems are needed to be identified and discussed with respect to ethical issues and the future roles of professionals and specialists for their wider application of AI.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.834-841
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• 2022

Recently, applying artificial intelligence technologies in various fields of production has drawn an upsurge of research interest due to the increase for smart factory and artificial intelligence technologies. A great deal of effort is being made to introduce artificial intelligence algorithms into the defect detection task. Particularly, detection of defects on the surface of metal has a higher level of research interest compared to other materials (wood, plastics, fibers, etc.). In this paper, we compare and analyze the speed and performance of defect classification by combining machine learning techniques (Support Vector Machine, Softmax Regression, Decision Tree) with dimensionality reduction algorithms (Principal Component Analysis, AutoEncoders) and two convolutional neural networks (proposed method, ResNet). To validate and compare the performance and speed of the algorithms, we have adopted two datasets ((i) public dataset, (ii) actual dataset), and on the basis of the results, the most efficient algorithm is determined.

• Journal of the Korea Society for Simulation
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• v.30 no.3
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• pp.1-9
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• 2021

Commander and staffs on the battlefield are aware of the situation and, based on the results, they perform military activities through their military decisions. Recently, with the development of information technology, the demand for artificial intelligence to support military decisions has increased. It is essential to identify, collect, and pre-process the data set for reinforcement learning to utilize artificial intelligence. However, data on enemies lacking in terms of accuracy, timeliness, and abundance is not suitable for use as AI learning data, so a training model is needed to collect AI learning data. In this paper, a methodology for learning artificial intelligence was presented using the constructive wargame model exercise data. First, the role and scope of artificial intelligence to support the commander and staff in the military decision-making process were specified, and to train artificial intelligence according to the role, learning data was identified in the Chang-Jo 21 model exercise data and the learning results were simulated. The simulation data set was created as imaginary sample data, and the doctrine of ROK Army, which is restricted to disclosure, was utilized with US Army's doctrine that can be collected on the Internet.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.269-274
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• 2021

With the development of artificial intelligence, society is moving to a different world. As a result, amid growing interest in artificial intelligence education, research on how to teach artificial intelligence is also being conducted more actively in Korea. However, a lot of research is being conducted around the upper grades of elementary school, and curriculum and programs for the lower grades are insufficient. Therefore, this study developed an artificial intelligence program for lower grades. Among them, it was developed focusing on artificial intelligence image recognition. It compares image recognition methods of people, animals, and computers, identifies the characteristics of fallen leaves, and helps them understand the image recognition process of artificial intelligence by classifying them according to the characteristics of fallen leaves. I hope this program will help elementary school students understand the image recognition principle of artificial intelligence in the future.

• Proceedings of the IEEK Conference
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• summer
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• pp.421-426
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• 2004

Analyzing adaptive possibilities of agents in multi-agents system, we have discovered new aspects of ambient intelligence in distributed modular systems using intelligent building blocks (I-BLOCKS) [1]. This paper describes early scientific researches related to technical design, applicable experiments and evaluation of adaptive processing and information interaction among I-BLOCKS allowing users to easily develop ambient intelligence applications. The processing technology presented in this paper is embedded inside each DUPLO1 brick by microprocessor as well as selected sensors and actuators in addition. Behaviors of an I-BLOCKS modular structure are defined by the internal processing functionality of each I-Blocks in such structure and communication capacities between I-BLOCKS. Users of the I-BLOCKS system can do 'programming by building' and thereby create specific functionalities of a modular structure of intelligent artefacts without the need to learn and use traditional programming language. From investigating different effects of modem artificial intelligence, I-BLOCKS we have developed might possibly contain potential possibilities for developing applications in ambient intelligence (AmI) environments. To illustrate these possibilities, the paper presents a range of different experimental scenarios in which I-BLOCKS have been used to set-up reconfigurable modular systems. The paper also reports briefly about earlier experiments of I-BLOCKS in different research fields, allowing users to construct AmI applications by a just defined concept of modular artefacts [3].

• Journal of Digital Convergence
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• v.11 no.5
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• pp.145-158
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• 2013

I estimate stock prices of listed companies using financial information and Ohlson model, which is used for the evaluation of company value. Furthermore, I use the artificial neural network, one of artificial intelligence systems, which are not based on linear relationship between variables, to estimate stock prices of listed companies. By reapplying this in estimating stock prices of newly listed companies, I evaluate the appropriateness in stock valuation with such methods. The result of practical analysis of this study is as follows. On the top of that, the multiplier for the actual stock price is accounted by generating the estimated stock prices based on the artificial neural network model. As a result of the comparison of two multipliers, the estimated stock prices by the artificial neural network model does not show statistically difference with the actual stock prices. Given that, the estimated stock price with artificial neural network is close to the actual stock prices rather than the estimated stock prices with Ohlson model.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.289-294
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• 2021

With the development of artificial intelligence, a wave of the 4th industrial revolution is taking place around the world. With the technologies such as big data and Internet of Things-based artificial intelligence, we are heading to a hyper-connected society where everything converges into one. Accordingly as educational talents in the era of artificial intelligence, we are pursuing the cultivation of creative convergence-type talents and emotional creative talents. With human creativity and emotion at the center, we should be able to collaborate with artificial intelligence and create new things by converging knowledge in various fields. By developing a program that combines humanities-oriented Korean language with engineering-oriented artificial intelligence, this research attempted to help students experience solving problems creatively by combining humanistic knowledge with engineering thinking skills. The educational program consists of two kinds of contents(i.e., "Books with AI" and "A Play with AI") and 15 classes that provide students with opportunities to solve humanities problems with artificial intelligence.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.85-91
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• 2024

Currently, generative artificial intelligence is a hot topic around the world. Generative artificial intelligence creates various images, art, video clips, advertisements, etc. The problem is that it is very difficult to verify the internal work of artificial intelligence. As a requirements engineer, I attempt to create a toon image by applying linguistic mechanisms to the current issue. This is combined with the UML object model through the semantic role analysis technique of linguists Chomsky and Fillmore. Then, the derived properties are linked to the toon creation template. This is to ensure productivity based on reusability rather than creativity in toon engineering. In the future, we plan to increase toon image productivity by incorporating software development processes and reusability.

• Electronics and Telecommunications Trends
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• v.39 no.5
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• pp.21-30
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• 2024

Memory can refer to a storage device that collects data, and it has evolved to increase the reading/writing speed and reduce the power consumption. As large amounts of data are processed by artificial intelligence services, the memory data capacity requires expansion. Dynamic random-access memory (DRAM) is the most widely used type of memory. In particular, graphics double date rate and high-bandwidth memory allow to quickly transfer large amounts of data and are used as memory solutions for artificial intelligence semiconductors. We analyze development trends in DRAM from the perspectives of processing speed and power consumption. We summarize the characteristics required for next-generation memory by comparing DRAM and other types of memory implementations. Moreover, we examine the shortcomings of DRAM and infer a next-generation memory for their compensation. We also describe the operating principles of spin-torque transfer magnetic random access memory, which may replace DRAM in next-generation devices, and explain its characteristics and advantages.