• 대한약학회:학술대회논문집
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• 대한약학회 2002년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.1
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• pp.131.1-131.1
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• 2002

• International Journal of Advanced Culture Technology
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• 제6권1호
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• pp.42-49
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• 2018

In this study, we tried to reveal the state of stillness of Cho Ji-Hoon's poem "Silent Night 1" as a healing modifier. The language of poem is synaptically linked to the calmness emotion of the human body, seeking a principle that leads to a state of healing. Therefore, this study was carried out for the purpose of applying the principle to literary therapy program. The silent signal embedded in the poem is encoded into the signals of the sound as it is synapsed to the human body. Encoding of auditory nerves by poem lines is like a Morse code that word and word leave in the human body. The action potential of the auditory nerve is further activated by the potential difference between the word and the word represented by the neural network, such as a Morse code, which is accessed to the human body by such a path. There is worked as amplified potential difference between the words perceived by a sound which is synapsed to the human body and by a silence which is synapsed to the human body. The phenomenon of the words approaching the human body and setting the absence of sound and amplifying the sound is because the words amplifies the Morse codes in the human neural network. At this time, the signals overlap each other. Thereby this poem is increasing the amplitude of the sound. This overlapping of auditory signals appears and amplifies the catharsis. If this Cho Ji-Hoon Poem's principle is applied to literary therapy program in the future, more effective treatment will be done.

• 환경영향평가
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• 제12권4호
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• pp.291-302
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• 2003

This paper examined the impacts of the regional developments and dwellers behavior on the Seacoast. Seacoast features a variety of landforms which are created by the action of waves and tidal flows. The coastal landforms are found mainly in the interface between land and sea. Although erosional landforms constitute prominent landscape features as sea stack, sea arch, and rock cliff do, it is nonetheless the depositional features such as beaches, tidal flats, offshore bars, deltas, sanddunes, and coastal plains that have various ramifications for human communities. Among these, beaches and coastal sanddunes are special in that their formation is attributable to the combined action of waves, tidal flows, and winds. The main line of discussion in this dissertation is concerned with the transformation of group of beaches sanddunes along the coastline of Chungcheong-Namdo Province. To some extent, the erosion of coastal dunes has been a global phenomenon. The degradation process occurs most actively when the spring tides attack beaches, berms, and foredunes. Also involved in the transformation of coastal dunes are factors of human agency. The extent, speed, and pattern of their morphological changes are a function of land-use pattern. The reclamation of swale and the exploitation of sands as construction material and silica sand, for example, ruin the feature of coastal dunes.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1997년도 추계학술대회논문집
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• pp.249-259
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• 1997

As the gap between competing products narrows in terms of performance and quality, the product usability is rapidly becoming a new dimension of product design as the key to offering distinctive value to the customer. Because the user interface is important, not only for the user but also for the efficiency of te whole organiation, system designers require increasingly precise evaluation methods to determine how effective and usable human-product interface is. In this study a new methodology named usability analysis diagram(UAD), for evaluating usability of human-product interface systematically, was developed. UAD is a top-down flow diaagram of a human-product interaction, in ehichfour basic elements - perception, understanding, intellectual decision and action - were classified and then represented by a particular symbol for each. The usability of the product is assessed by the frequency of each symbol in a diagram which represents a sequence of cognitive and physical activities of users during the use of the product, and by the level of difficulty that is classif- ied in three levels in terms of easiness of perception, understanding and action. In order to test validity of the proposed UAD in a real situation, a case study was performed on two different cameras, automatic and manual, and their usability was successfully evaluated and compared.

• 한국산학기술학회논문지
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• 제16권11호
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• pp.7508-7512
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• 2015

뇌파로 의도를 접속하여 기계를 작동하는 뇌-기기 접속(Brain-Computer Interface, BCI) 기반의 인간-로봇상호작용(Human-Robot Interaction, HRI) 플랫폼을 제안한다. 사람의 뇌파로 의도를 포착하고 포착된 뇌파 신호에서 의도를 추출하거나 연관시키고 추출된 의도로 기기를 작동하게 하는 포착, 처리, 실행을 수행하는 플랫폼의 설계, 운용 및 구현 과정을 소개한다. 제안된 플랫폼의 구현 사례로 처리기에 구현된 상호작용 게임과 처리기를 통한 외부 장치 제어가 기술되었다. BCI 기반 플랫폼의 의도와 감지 사이의 신뢰성을 확보하기 위한 다양한 시도들을 소개한다. 제안된 플랫폼과 구현 사례는 BCI 기반의 새로운 기기 제어 작동 방식의 실현으로 확장될 것으로 기대된다.

• 전자통신동향분석
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• 제36권4호
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• pp.92-102
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• 2021

Outdoor sports activities have been restricted by serious air pollution, such as fine dust and yellow dust, and abnormal meteorological change, such as heatwave and heavy snow. These environmental problems have rapidly increased the demand for indoor sports activities. Virtual sports, such as virtual golf, virtual baseball, virtual soccer, etc., allow playing various sports games without going outdoors. Indoor sports industries and markets have seen rapid growth since the advent of virtual sports. Most virtual sports platforms use screen-based virtual reality techniques, which are why they are called screen sports. However, these platforms cannot support various sports games, especially virtual match games, such as squash, boxing, and so on, because existing screen-based virtual reality sports techniques use real balls and players. This article presents screen-based haptic-augmented reality technologies for a new virtual sports platform. The new platform does not use real balls and players to solve the limitations of previous platforms. Here, various technologies, including human motion tracking, human action recognition, haptic feedback, screen-based augmented-reality systems, and augmented-reality sports content, are unified for the new virtual sports platform. From these haptic-augmented reality technologies, the proposed platform supports sports games, including indoor virtual matches, that existing virtual sports platforms cannot support.

• Journal of Applied Biological Chemistry
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• 제65권3호
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• pp.167-172
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• 2022

Pathophysiological reaction of platelets in the blood vessel is an indispensable part of thrombosis and cardiovascular disease, which is the most common cause of death in the world. In this study, we performed in vitro assays to evaluate antiplatelet activity of artemether in human platelets and attempted to identify the mechanism responsible for protein phosphorylation. Artemether is a derivative of artemisinin, known as an active ingredient of Artemisia annua, which has been reported to be effective in treating malaria, and is known to function through antioxidant and metabolic enzyme inhibition. However, the role of artemether in platelet activation and aggregation and the mechanism of action of artemether in collagen-induced human platelets are not known until now. In this study, the effect of artesunate on collagen-induced human platelet aggregation was confirmed and the mechanism of action of artemether was clarified. Artemether inhibited the phosphorylation of PI3K/Akt and Mitogen-activated protein kinases, which are phosphoproteins that are known to act in the signal transduction process when platelets are activated. In addition, artemether decreased TXA₂ production and decreased granule secretion in platelets such as ATP and serotonin release. As a result, artemether strongly inhibited platelet aggregation induced by collagen, a strong aggregation inducer secreted from vascular endothelial cells, with an IC₅₀ of 157.92 μM. These results suggest that artemether has value as an effective antithrombotic agent for inhibiting the activation and aggregation of human platelets through vascular injury.

• ETRI Journal
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• 제44권2호
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• pp.286-299
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• 2022

Human activity recognition in real time is a challenging task. Recently, a plethora of studies has been proposed using deep learning architectures. The implementation of these architectures requires the high computing power of the machine and a massive database. However, handcrafted features-based machine learning models need less computing power and very accurate where features are effectively extracted. In this study, we propose a handcrafted model based on three-dimensional sequential skeleton data. The human body skeleton movement over a frame is computed through joint positions in a frame. The joints of these skeletal frames are projected into two-dimensional space, forming a "movement polygon." These polygons are further transformed into a one-dimensional space by computing amplitudes at different angles from the centroid of polygons. The feature vector is formed by the sampling of these amplitudes at different angles. The performance of the algorithm is evaluated using a support vector machine on four public datasets: MSR Action3D, Berkeley MHAD, TST Fall Detection, and NTU-RGB+D, and the highest accuracies achieved on these datasets are 94.13%, 93.34%, 95.7%, and 86.8%, respectively. These accuracies are compared with similar state-of-the-art and show superior performance.

• 대한안전경영과학회지
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• 제8권1호
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• pp.17-26
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• 2006

Basis frame-work's base in a semiconductor industry have gas, chemical, electricity and various facilities in bring to it. That it is a foundation by fire, power failure, blast, spill of toxicant huge by large size accident human and physical loss and damage because it can bring this efficient, connect with each kind mechanical, physical thing to prevent usefully need that control finding achievement factor of human factor of human action. Large size accident in a semiconductor industry to machine and human and it is involved that present, in system by safety interlock defect of machine is conclusion for error of behaviour. What is not construing in this study, do safety in a semiconductor industry to do improvement. Control human error analyzes in human control with and considers mechanical element and several elements. Also, apply achievement factor using O'conner Model by control method of human error. In analyze by failure mode effect using actuality example.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.751-770
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• 2019

Action recognition is an essential task in computer vision due to the variety of prospective applications, such as security surveillance, machine learning, and human-computer interaction. The availability of more video data than ever before and the lofty performance of deep convolutional neural networks also make it essential for action recognition in video. Unfortunately, limited crafted video features and the scarcity of benchmark datasets make it challenging to address the multi-person action recognition task in video data. In this work, we propose a deep convolutional neural network-based Effective Hybrid Learning (EHL) framework for two-person interaction classification in video data. Our approach exploits a pre-trained network model (the VGG16 from the University of Oxford Visual Geometry Group) and extends the Faster R-CNN (region-based convolutional neural network a state-of-the-art detector for image classification). We broaden a semi-supervised learning method combined with an active learning method to improve overall performance. Numerous types of two-person interactions exist in the real world, which makes this a challenging task. In our experiment, we consider a limited number of actions, such as hugging, fighting, linking arms, talking, and kidnapping in two environment such simple and complex. We show that our trained model with an active semi-supervised learning architecture gradually improves the performance. In a simple environment using an Intelligent Technology Laboratory (ITLab) dataset from Inha University, performance increased to 95.6% accuracy, and in a complex environment, performance reached 81% accuracy. Our method reduces data-labeling time, compared to supervised learning methods, for the ITLab dataset. We also conduct extensive experiment on Human Action Recognition benchmarks such as UT-Interaction dataset, HMDB51 dataset and obtain better performance than state-of-the-art approaches.