• KSBB Journal
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• v.32 no.2
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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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• v.10 no.3
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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.

• Smart Media Journal
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• v.6 no.3
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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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• v.35 no.6
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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.

• Journal of Korea Multimedia Society
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• v.21 no.1
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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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• v.21 no.1
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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.

• Journal of Korea Multimedia Society
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• v.25 no.8
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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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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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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• 2003.10a
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• pp.335-339
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• 2003

The aim of this study is to optimize the monolayer cultivation of human articular chondrocytes in serum-free media. For this purpose, chondrocytes were isolated from human articular cartilage and monolayer cultures were performed in DMEM/F12 medium with 10% fetal bovine serum (FBS) or serum-free media (SFM) containing various supplements and epidermal growth factor (EGF). Western blotting analysis, RT-PCR, dimethylmethylene blue (DMB) assay were carried out to evaluate the synthesis of collagen type II (Col. II) and glycosaminoglycans (GAGs). We observed that SFM with EGF stimulated the cell growth while the amounts of synthesized GAGs and Col. II were decreased gradually. However, the Col. II mRNA level was increased when the SFM was replaced by media containing 10% FBS. This study suggests that it is possible to obtain large amount of human articular chondrocytes by short-term monolayer cultures in SFM.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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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.