• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.57-59
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• 1994

In this paper, we present the software part of the intelligent data processing unit (IDPU), which plays an important role in SiMACS. The software system processes ECG, EEG, EMG, blood pressure, respiration, temperature signals, and extracts some information about patient conditions. It displays the patient condition information and the signal data synchronously, and manages them together with other patient personal data in a network-based client/server environment. The software system is designed in an object-oriented paradigm, and implemented in C++ as a window-based application program.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.133-137
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• 2005

In this paper, we investigate visual and quantitative analysis of different tastes in the liquids using multi-array chemical sensor (MACS) based on the ion-selective electrodes (ISEs), which is so called the electronic tongue (E-Tongue) system. We apply the Fuzzy C-means (FCM) algorithm combined with Principal Component Analysis (PCA), which can be used to reduce multi-dimensional data to two- or three-dimensional data, to classify visually data patterns detected by E-Tongue system. The proposed technique can be determined the cluster centers and membership grade of patterns through the unsupervised way. The membership grade of an unknown pattern, which does not shown previously, can be visually and analytically determined. Throughout the experimental trails, the E-tongue system combined with the proposed algorithms is demonstrated robust performance for visual and quantitative analysis for different tastes in the liquids.

• Food Science of Animal Resources
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• v.40 no.5
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• pp.852-859
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• 2020

The muscle stem cells of domestic animals are of interest to researchers in the food and biotechnology industries for the production of cultured meat. For producing cultured meat, it is crucial for muscle stem cells to be efficiently isolated and stably maintained in vitro on a large scale. In the present study, we aimed to optimize the method for the enrichment of pig muscle stem cells using a magnetic-activated cell sorting (MACS) system. Pig muscle stem cells were collected from the biceps femoris muscles of 14 d-old pigs of three breeds [Landrace×Yorkshire×Duroc (LYD), Berkshire, and Korean native pigs] and cultured in skeletal muscle growth medium-2 (SkGM-2) supplemented with epidermal growth factor (EGF), dexamethasone, and a p38 inhibitor (SB203580). Approximately 30% of total cultured cells were nonmyogenic cells in the absence of purification in our system, as determined by immunostaining for cluster of differentiation 56 (CD56) and CD29, which are known markers of muscle stem cells. Interestingly, following MACS isolation using the CD29 antibody, the proportion of CD56⁺/CD29⁺ muscle stem cells was significantly increased (91.5±2.40%), and the proportion of CD56 single-positive nonmyogenic cells was dramatically decreased. Furthermore, we verified that this method worked well for purifying muscle stem cells in the three pig breeds. Accordingly, we found that CD29 is a valuable candidate among the various marker genes for the isolation of pig muscle stem cells and developed a simple sorting method based on a single antibody to this protein.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.53-56
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• 1994

We have developed biological signal measurement modules and data acquisition and control card for a biological signal measurement, archiving, and communication system (SiMACS). Biological signals included in this system are ECG, EEG, EMG, invasive blood pressure, respiration, and temperature. Parameters of each module can be controlled by PC-base IDPU (intelligent data processing unit) through a data acquisition and control card. The data acquisition and control card can collect up to 16 channels of biological signals with sampling rate of $50\;{\sim}\;2,000Hz$ and 12-bit resolution. All measurement moduls and data acquisition functions are controlled by microcontroller which receives commands from PC. All data transfers among PC, microcontroller, and ADC are done through a shared RAM access by polling method for real rime operation.

• Journal of the Korean Society of Physical Medicine
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• v.14 no.2
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• pp.97-105
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• 2019

PURPOSE: This study examined the factors related to school-based activity performance in school-aged children with spastic cerebral palsy (CP). METHODS: The Gross Motor Function Systems (GMFCS), Manual Ability Classification System (MACS), Communication Function Classification System (CFCS) as functional classifications, and the physical activity performance of the School Function Assessment (SFA) were measured in 79 children with spastic CP to assess the student's performance of specific school-related functional activities. RESULTS: All the function classification systems were correlated significantly with the physical activity performance of the SFA ($r_s=-.47$ to -.80) (p<.05). The MACS (${\beta}=-.59$), GMFCS (${\beta}=-.23$), CFCS (${\beta}=-.21$), and age (${\beta}=-.15$) in order were predictors of the physical activity performance of the SFA (84.8%)(p<.05). CONCLUSION: These functional classification systems can be used to predict the school-based activity performance in school-aged children with CP. In addition, they can contribute to the selection of areas for intensive interventions to improve the school-based activity performance.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.428-435
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• 2024

In this paper, a human activity regeneration (HAR) system based on multiple input multiple output frequency modulation continuous wave (MIMO FMCW) radar was designed and implemented. Using point cloud data from MIMO radar sensors has advantages in terms of privacy, safety, and accuracy. For the implementation of the HAR system, a customized neural network based on PointPillars and depthwise separate convolutional neural network (DS-CNN) was developed. By processing high-resolution point cloud data through a lightweight network, high accuracy and efficiency were achieved. As a result, the accuracy of 98.27% and the computational complexity of 11.27M multiply-accumulates (Macs) were achieved. In addition, the developed neural network model was implemented on Raspberry-Pi embedded system and it was confirmed that point cloud data can be processed at a speed of up to 8 fps.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.60-62
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• 1994

In this paper, we present a signal analysis workstation in which the user can scrutinize and quantify biological signals, observe the effects of various signal processing algorithms on them, and eventually get some interpretation of clinical use. Within the system, the user can also access all the information in the central data base, such as patient personal information, biological signal information, and insert his interpretation results obtained into the data base after his careful observation. The software system is designed in an object-oriented paradigm, and written in C++ as a window-based application program.

• Journal of information and communication convergence engineering
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• v.12 no.1
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• pp.14-18
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• 2014

A recent major development in computer technology is the advent of wearable computer systems. Wearable computer systems employ a wireless universal serial bus (WUSB), which refers to a combination of USB with the WiMedia wireless technical specifications. In this study, we focus on an integrated system of WUSB over wireless body area networks (WBANs) for wireless wearable computer systems. However, current WBAN MACs do not have well-defined quality of service (QoS) mapping and resource allocation mechanisms to support multimedia streams with the requested QoS parameters. To solve this problem, we propose a novel QoS-aware time slot allocation method. The proposed method provides fair and adaptive QoS provisioning to isochronous streams according to current traffic loads and their requested QoS parameters by executing a QoS satisfaction algorithm at the WUSB/WBAN host. The simulation results show that the proposed method improves the efficiency of time slot utilization while maximizing QoS provisioning.

• Journal of KIISE
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• v.44 no.2
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• pp.213-222
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• 2017

The Internet of Things (IoT) technology is rapidly developing in recent years, and is applicable to various fields. A smart factory is one wherein all the components are organically connected to each other via a WSN, using an intelligent operating system and the IoT. A smart factory technology is used for flexible process automation and custom manufacturing, and hence needs adaptive network management for frequent network fluctuations. Moreover, ensuring the timeliness of the data collected through sensor nodes is crucial. In order to ensure network timeliness, the power consumption for information exchange increases. In this paper, we propose an IEEE 802.15.4e DSME-based distributed scheduling algorithm for mobility support, and we evaluate various performance metrics. The proposed algorithm adaptively assigns communication slots by analyzing the network traffic of each node, and improves the network reliability and timeliness. The experimental results indicate that the throughput of the DSME MAC protocol is better than the IEEE 802.15.4e TSCH and the legacy slotted CSMA/CA in large networks with more than 30 nodes. Also, the proposed algorithm improves the throughput by 15%, higher than other MACs including the original DSME. Experimentally, we confirm that the algorithm reduces power consumption by improving the availability of communication slots. The proposed algorithm improves the power consumption by 40%, higher than other MACs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.11
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• pp.1162-1169
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• 2012

One of the important operational requirements for mission critical Ethernet networked system is having the fault tolerant capability. Such capability can be obtained by equipping multiport Network Interface Card (NIC) in each node in the system. Conventional NIC uses two or more Media Access Controls (MACs) and a co-processor for the MAC switching whenever an active port fails. Since firmware is needed for the co-processor, longer fail-over switching and degraded throughput can be generally expected. Furthermore the system upgrading requiring the firmware revision in each tactical node demands high cost. In this paper we propose a novel single MAC based NIC that does not use a co-processor, but just use general discrete building blocks such as MAC chip and switching chip, which results in better performances than conventional method. Experimental results validate our scheme.