• Journal of Environmental Science International
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• v.11 no.3
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• pp.201-207
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• 2002

This study was carried out to evaluate the artificial neural network algorithm for water quality forecasting in Chungju lake, north Chungcheong province. Multi-layer perceptron(MLP) was used to train artificial neural networks. MLP was composed of one input layer, two hidden layers and one output layer. Transfer functions of the hidden layer were sigmoid and linear function. The number of node in the hidden layer was decided by trial and error method. It showed that appropriate node number in the hidden layer is 10 for pH training, 15 for DO and BOD, respectively. Reliability index was used to verify for the forecasting power. Considering some outlying data, artificial neural network fitted well between actual water quality data and computed data by artificial neural networks.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.11a
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• pp.32-33
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• 2013

This study was a result of laboratory test to confirm the porperties of concrete containing the domestic artificial lightweight aggregate. The domestic artificial lightweight aggregate is made with bottom ash which waste material in the thermal power plant. In the experimental result air contents of fresh concrete was measured lower than other artificial lightweight aggregate. This air contents is important for retaining the resistance of freezing and thawing. Therefore air contents of concrete will be considered for retaining the resistance of freezing and thawing when manufacture the concrete containing the domestic artificial aggregate.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.8
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• pp.471-481
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• 2003

The acts of biological immune system are similar to the navigation for autonomous mobile robots under dynamically changing environments. In recent years, many researchers have studied navigation algorithms using artificial immune networks. Conventional artificial immune algorithms consist of an obstacle-avoidance behavior and a goal-reaching behavior. To select a proper action, the navigation algorithm should combine the obstacle-avoidance behavior with the goal-reaching behavior. In this paper, the neural network is employed to combine the behaviors. The neural network is trained with the surrounding information. the outputs of the neural network are proper combinational weights of the behaviors in real-time. Also, a velocity control algorithm is constructed with the artificial immune network. Through a simulation study and experimental results for a autonomous mobile robot, we have shown the validity of the proposed navigation algorithm.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.10a
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• pp.277-282
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• 2002

This study was performed to find out basic function of artificial upwelling structures. Generation of artificial upwelling current was affected by size of structures, incident current and porosity. when stratification parameters was about 3.0, relative height(hs/h) of structures was $0.125{\sim}0.15$, stable artificial upwelling current was generated in the back-side of structures. when porosity is lower than 50%, the effect of artificial upwelling structure was to be better than little by little.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.7 no.2
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• pp.21-35
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• 2004

A questionnaire survey from 200 visitors and 100 residents was carried out to establish the management plan of the artificial structures constructed in valley within Bughansan National Park. According to the result of the survey respondents realized that the valley ecosystem could be damaged by artificial structures, but not pollutants of stream water. About 60 % of the respondents felt uncomfortable by artificial cement constructures and about 22 % was concerned about negative effect of valley ecosystem by the constructures. The results categorized by management body, management system and management cost indicate that the artificial constructures should be managed in terms of the safety and conservation of valley ecosystem.

• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.193-199
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• 2012

Worldwide cardiovascular diseases are the major cause of death. Aside from heart transplants, which are limited due to the availability of human donor hearts, artificial hearts are the only therapy available for terminal heart diseases. For various reasons, a total implantable artificial heart is desirable. But the limited space in the human thorax sets rigorous restrictions on the weight and dimensions of the device. Nevertheless, the appropriate functionality of the artificial heart must be ensured and blood damage must be prevented. These requirements set further restrictions to the drive of this device. In the this paper, two optimization methods, namely, the manual parameter variation and Differential Evolution algorithm, are presented and applied to match the specifications of an artificial heart.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.307-312
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• 2021

Artificial Intelligence has a long history and is used in various fields including image recognition and automatic translation. Therefore, when we first encounter artificial intelligence, many terms, concepts and technologies often have difficulty in setting or implementing research direction. This study summarized important concepts related to artificial intelligence and summarized the progress of the past 60 years to help researcher suffering from these difficulties. Through this, it is possible to establish the basis for the use of vast artificial intelligence technologies and establish the right direction for research.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.239-244
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• 2022

The study aimed to build a program in activities for early childhood students to develop some of the basic skills necessary for the age of artificial intelligence, to achieve the objectives of the study , the researcher used the experimental design, and the research sample consisted of 37 early childhood students. The study used the following tools: Experimental treatment subject: the proposed program in the activities, Measurement and evaluation tool: testing the basic skills needed for the age of artificial intelligence. The study concluded several results: There is a statistically significant difference (α≤0.05) between the average grades of the early childhood students in the research group in the tribal and remote measurements to test the basic skills necessary for the age of artificial intelligence in favor of the students grades in the dimensional measurements. Practical application of the study through benefiting from the proposed program of activities prepared in the current study in planning and implementing activities to develop the basic skills necessary for the age of artificial intelligence among early childhood students.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.590-593
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• 2022

최근 코로나바이러스감염증-19(COVID-19)로 인해서 다양한 비대면 서비스가 증가하고 있는데 그 중에서 사람과 인공지능 간 의사소통하여 정보를 얻는 대화 시스템이 대표적인 서비스이다. 대화 시스템은 입력되는 단일 문장에 대한 정보만을 응답하기 때문에 이전 대화의 정보를 알기 위해서는 질문했던 내용을 다시 입력해야 하는 문제점이 있다. 이런 문제를 해결하고 대화 진행에 도움을 주기 위해서 본 논문에서는 대화 내 문장들의 다중 의도 탐지를 통한 공통 대화 주제 식별 시스템을 제안한다.