• KSBB Journal
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• 제32권2호
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• pp.90-95
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• 2017

Mammalian cell cultures have been used extensively to produce proteins for therapeutic agent because of their ability to perform post-translational modification including glycosylation. To produce recombinant protein, many factors and parameter are considered such as media composition, host cell type, and culture process. In this study, recombinant human erythropoietin (rhEPO) producing cell line was established by using glutamine synthetase system. To reduce serum concentration in media, we compared direct adaptation with step adaptation. Cell growth was faster in step adaptation. In low-level serum media, there were insufficient glucose for cell growth. Thus, we added glucose in low-level serum media from 2 g/L to 4.5 g/L. Titer of rhEPO was higher than other conditions at 4.5 g/L of glucose. Additionally, N-methyl-D-aspartate (NMDA), 13-cis-retinal, and pluronic F-68 (PF-68) were added to enhance productivity in CHO cell cultures. In conclusion, we applied CHO cell producing rhEPO to low-level of serum in media using step-adaptation. Also, we confirmed positive effect of NMDA, 13-cis-retinal, and PF-68.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.1264-1274
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• 2015

Human action recognition received many interest in the computer vision community. Most of the existing methods focus on either construct robust descriptor from the temporal domain, or computational method to exploit the discriminative power of the descriptor. In this paper we explore the idea of using local action attributes to form an action descriptor, where an action is no longer characterized with the motion changes in the temporal domain but the local semantic description of the action. We propose an novel framework where introduces local action attributes to represent an action for the final human action categorization. The local action attributes are defined for each body part which are independent from the global action. The resulting attribute descriptor is used to jointly model human action to achieve robust performance. In addition, we conduct some study on the impact of using body local and global low-level feature for the aforementioned attributes. Experiments on the KTH dataset and the MV-TJU dataset show that our local action attribute based descriptor improve action recognition performance.

• 스마트미디어저널
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• 제6권3호
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• pp.49-56
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• 2017

Images and Videos that include the human face contain a lot of information. Therefore, accurately extracting human face is a very important issue in the field of computer vision. However, in real life, human faces have various shapes and textures. To adapt to these variations, A model-based approach is one of the best ways in which unknown data can be represented by the model in which it is built. However, the model-based approach has its weaknesses when the motion between two frames is big, it can be either a sudden change of pose or moving with fast speed. In this paper, we propose an enhanced human face-tracking model. This approach included human face detection and motion estimation using Cascaded Convolutional Neural Networks, and continuous human face tracking and modeling correction steps using the Active Appearance Model. A proposed system detects human face in the first input frame and initializes the models. On later frames, Cascaded CNN face detection is used to estimate the target motion such as location or pose before applying the old model and fit new target.

• ETRI Journal
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• 제35권6호
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• pp.1001-1010
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• 2013

A sensible media simulation system for automobiles is introduced to open up new possibilities for an in-car entertainment system. In this paper, the system architecture is presented, which includes a virtuality-to-reality adaptation scheme. Standard data schemes for context and control information from the International Standard MPEG-V (ISO/IEC 23005) are introduced to explain the details of data formats, which are interchangeable in the system. A sensible media simulator and the implementation of a sensory device are presented to prove the effectiveness of the proposed system. Finally, a correlation between learning styles and sensory effects (that is, wind and vibration effects) is statistically analyzed using the proposed system. The experiment results show that the level of satisfaction with the sensory effects is unaffected overall by the learning styles of the test subjects. Stimulations by vibration effects, however, generate more satisfaction in people with a high tactile perception level or a low visual perception level.

• 한국멀티미디어학회논문지
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• 제21권1호
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• pp.51-60
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• 2018

We present a real-time interactive particle-art with human motion based on computer vision techniques. We used computer vision techniques to reduce the number of equipments that required for media art appreciations. We analyze pros and cons of various computer vision methods that can adapted to interactive digital media art. In our system, background subtraction is applied to search an audience. The audience image is changed into particles with grid cells. Optical flow is used to detect the motion of the audience and create particle effects. Also we define a virtual button for interaction. This paper introduces a series of computer vision modules to build the interactive digital media art contents which can be easily configurated with a camera sensor.

• Journal of information and communication convergence engineering
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• 제21권1호
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• pp.98-102
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• 2023

This paper presents a study on how augmenting semi-synthetic image data improves the performance of human detection algorithms. In the field of object detection, securing a high-quality data set plays the most important role in training deep learning algorithms. Recently, the acquisition of real image data has become time consuming and expensive; therefore, research using synthesized data has been conducted. Synthetic data haves the advantage of being able to generate a vast amount of data and accurately label it. However, the utility of synthetic data in human detection has not yet been demonstrated. Therefore, we use You Only Look Once (YOLO), the object detection algorithm most commonly used, to experimentally analyze the effect of synthetic data augmentation on human detection performance. As a result of training YOLO using the Penn-Fudan dataset, it was shown that the YOLO network model trained on a dataset augmented with synthetic data provided high-performance results in terms of the Precision-Recall Curve and F1-Confidence Curve.

• 한국멀티미디어학회논문지
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• 제25권8호
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• pp.1049-1058
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• 2022

HAR(Human Action Recognition) such as anomaly and object detection has become a trend in research field(s) that focus on utilizing Artificial Intelligence (AI) methods to analyze patterns of human action in crime-ridden area(s), media services, and industrial facilities. Especially, in real-time system(s) using video streaming data, HAR has become a more important AI-based research field in application development and many different research fields using HAR have currently been developed and improved. In this paper, we propose and analyze a deep-learning-based HAR that provides more efficient scheme(s) using an intelligent AI models, such system can be applied to media services using RGB video streaming data usage without feature extraction pre-processing. For the method, we adopt Slowfast based on the Deep Neural Network(DNN) model under an open dataset(HMDB-51 or UCF101) for improvement in prediction accuracy.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1997년도 Proceedings International Workshop on New Video Media Technology
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• pp.13-18
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• 1997

Each reproducing speech signal has each particular signal property, because of the processing of encoding and decoding for communications through various media. In this paper, we examine the correlation between speech signal quality and sensory pleasure for the sensory improvement of that signal. In experiments, we evaluate the quality of speech signals through various media by psychological auditory test and physical features of these signals.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2003년도 생물공학의 동향(XIII)
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• pp.335-339
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• 2003

본 연구에서는 연골조직으로부터 세포를 분리한 후 10%의 혈청 첨가 배지와 무혈청 배지에서의 세포 성장속도, GAGs 합성 및 Col. II의 발현을 확인하였다. EGF를 첨가한 무혈청 배지를 연골세포의 증식에 매우 효과적이었으나 GAGs 합성 및 Col. II 의 합성을 저해하였다. 또한 무혈청 배지에서 배양한 세포를 차후 신체내로 이식한다면 연골세포의 특성인 Col. II를 재합성할 수 있음을 간접적으로 확인하였다. 이는 무혈청 배지를 이용하여 평판배양 시 짧은 기간 내 연골세포 치료제로서 가능한 세포수를 얻기 위한 모델로서 유용할 것으로 생각된다. 또한 계대배양에 따른 분화 및 형태의 변화 등의 문제점들은 생분해성 지지체와 연계하여 해결할 수 있을 것으로 생각되며, 차후 위의 SFM을 이용한 3D 배양에 대한 연구를 수행할 예정이다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 추계학술발표대회
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• pp.563-565
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• 2023

Acupuncture and acupressure apply needles or pressure to anatomical points for therapeutic benefit. The over 350 mapped acupuncture points in the human body can each treat various conditions, but anatomical variations make precisely locating these acupoints difficult. We propose a computer vision technique using the real-time hand and face tracking capabilities of the MediaPipe framework to identify acupoint locations. Our model detects anatomical facial and hand landmarks, and then maps these to corresponding acupoint regions. In summary, our proposed model facilitates precise acupoint localization for self-treatment and enhances practitioners' abilities to deliver targeted acupuncture and acupressure therapies.