• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.11-14
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• 1999

The forthcoming century will be the "era of cyber society" . In a virtual environment, a cyber character plays the role of an agent for the human being. In this paper, we introduce active researches of industries, universities, and research institutes in Korea. After Adam Soft Inc. presented a cyber singer,“Adam”, a few cyber characters have succeeded commercially through Internet, TV, CF, movies and etc. Some universities had their own characters to make fundamental researches in the fields of modeling, motion control, and VR. Research institutes have been funded recently to a cyber character related researches. This paper briefly reviews the recent research works, and future trends in Korea. in Korea.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.204-208
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• 2018

Comparison of different optimizer performance in photovoltaic power modeling using artificial neural deep learning techniques is described in this paper. Six different deep learning optimizers are tested for Long-Short-Term Memory networks in this study. The optimizers are namely Adam, Stochastic Gradient Descent, Root Mean Square Propagation, Adaptive Gradient, and some variants such as Adamax and Nadam. For comparing the optimization techniques, high and low fluctuated photovoltaic power output are examined and the power output is real data obtained from the site at Mokpo university. Using Python Keras version, we have developed the prediction program for the performance evaluation of the optimizations. The prediction error results of each optimizer in both high and low power cases shows that the Adam has better performance compared to the other optimizers.

• Proceedings of the Korean Society of Developmental Biology Conference
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• 2003.02a
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• pp.17-17
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• 2003

• Proceedings of the Korean Society of Developmental Biology Conference
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• 2003.02a
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• pp.30-30
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• 2003

• 방재와보험
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• s.103
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• pp.66-69
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• 2004

이 글은 Fire Provention Fire Engineers journal 2004년 5월에 수록된 Armando Herrera, Aron Adams의 글로, 저자들은 $특수점검자^{(주)}(special inspector)를 통해 제연시스템을 테스트하여 어떻게 시간과 금전을 절약할 수 있는지를 설명한다.

• 대한생식의학회:학술대회논문집
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• 2002.05a
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• pp.81.1-81.1
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• 2002

• Journal of Korean Philosophical Society
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• v.142
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• pp.27-50
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• 2017

When we lose our memories or when our self-identity becomes blurred, we may feel as if our mind has split into multiple minds. If someone makes another 'me' by copying my body and mind, how should two conscious 'I's change their credences? In this article, we present a new thought experiment that can be called the 'Two Adams Problem'. This thought experiment represents a piece of philosophical inquiry that speculates on the nature of self-consciousness information that 'I am awake now'. On Sunday evening, as soon as Adam falls asleep, the philosopher Roro makes another Adam by copying Adam's original body and mind. They sleep separately in another room. Within a minute, Roro throws a fair coin. If the coin lands heads up Roro wakes just one of the Adams up on Monday. If the coin lands tails up Roro wakes both Adams up. On Monday, at least one of the Adams will wake up. To what degree ought they believe that the outcome of the coin toss is heads? We will argue that the correct answer to this question is 1/2.

• Food Science of Animal Resources
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• v.30 no.1
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• pp.120-123
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• 2010

The standard method for somatic cell counts in goat milk is the direct microscopic method after a pyronin Y-methyl stain. It has been reported, however, that are found to differ by measuring methods, but. A total of forty eight goat milk samples from eight farms were compared by pyronin Y-methyl stain, ADAM-SCC in National Institute of Animal Science, and Somacount 500 in Chungbuk Veterinary Service. The average SCC of the samples was $7.3{\times}10^5$ cells/mL by pyronin Y-methyl stain, $4.9{\times}10^5$ cells/mL by ADAM-SCC, and $11.6{\times}10^5$ cells/mL by Somacount 500. The correlations between the methods were not significant. SCC measuring equipment should be developed for reducing the SCC in goat milk, and pyronin Y-methyl green stain for estimating SCC in goat milk should be included in NVRQS Notice for livestock products processing and composition standards.

• Journal of Korean Philosophical Society
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• no.114
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• pp.305-335
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• 2016

In the eighteenth century, the scottish philosophers Francis Hutcheson, David Hume and Adam Smith share the idea that morality comes from moral sense, which is a feeling of approval or disapproval of agent's motive and action. However, they have the different views in explaining the mechanism that generates the moral sentiments. Hutcheson takes a moral sense to be a unique mental faculty that is innate to all humans, and regards it as being guaranteed by supernatural apparatus like divine Providence. Hume and Smith reject Hutcheson's concept of internal moral sense and take a stage further Hutcheson's projects of internalisation by naturalizing morality in terms of the principle of sympathy. It is widely held that Hume's moral sentimentalism is essentially similar to Adam Smith's. Though there are important points of contact between Smith's account of sympathy and Hume's, the differences are considerable. The chief of them lies in the fact that Hume grounds our approval of virtue on our recognition of its utility and convention, and Smith does not. Smith grounds our approval of virtue on the impartial spectator's judgment, i.e., conscience. Hence for Smith, the impartial spectator is the one that bridges the gap between particularity and universality and works the vehicle of practical reason. Given this, in this paper, first, I will clarify the difference between Hume's and Adam Smith's understandings of sympathy. Second, I will elucidate how they explain the process to produce the moral sentiments based on their understandings of sympathy. I shall finally explicate in what way Hume's and Smith's theories on sympathy work as moral normativity.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1329-1341
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• 2022

Destroying the marine environment and marine ecosystem and causing marine accidents, marine debris is generated every year, and among them, submerged marine debris is difficult to identify and collect because it is on the seabed. Therefore, deep-learning-based semantic segmentation was experimented on waste fish nets and waste ropes using underwater images to identify efficient collection and distribution. For segmentation, a high-resolution network (HRNet), a state-of-the-art deep learning technique, was used, and the performance of each optimizer was compared. In the segmentation result fish net, F1 score=(86.46%, 86.20%, 85.29%), IoU=(76.15%, 75.74%, 74.36%), For the rope F1 score=(80.49%, 80.48%, 77.86%), IoU=(67.35%, 67.33%, 63.75%) in the order of adaptive moment estimation (Adam), Momentum, and stochastic gradient descent (SGD). Adam's results were the highest in both fish net and rope. Through the research results, the evaluation of segmentation performance for each optimizer and the possibility of segmentation of marine debris in the latest deep learning technique were confirmed. Accordingly, it is judged that by applying the latest deep learning technique to the identification of submerged marine debris through underwater images, it will be helpful in estimating the distribution of marine sedimentation debris through more accurate and efficient identification than identification through the naked eye.