• Journal of Microbiology and Biotechnology
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• v.31 no.2
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• pp.197-206
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• 2021

microRNA-361-3p (miR-361-3p) is involved in the carcinogenesis of oral cancer and pancreatic catheter adenocarcinoma, and has anti-carcinogenic effects on non-small cell lung cancer (NSCLC). However, its effect on multiple myeloma (MM) is less reported. Here, we found that upregulating the expression of miR-361-3p inhibited MM cell viability and promoted MM apoptosis. We measured expressions of tumor necrosis factor receptor-associated factor 6 (TRAF6) and miR-361-3p in MM cells and detected the viability, colony formation rate, and apoptosis of MM cells. In addition, we measured expressions of apoptosis-related genes Bcl-2, Bax, and Cleaved caspase-3 (C caspase-3). The binding site between miR-361-3p and TRAF6 was predicted by TargetScan. Our results showed that miR-361-3p was low expressed in the plasma of MM patients and cell lines, while its overexpression inhibited viability and colony formation of MM cells and increased the cell apoptosis. Furthermore, TRAF6, which was predicted to be a target gene of miR-361-3p, was high-expressed in the plasma of patients and cell lines with MM. Rescue experiments demonstrated that the effect of TRAF6 on MM cells was opposite to that of miR-361-3p. Upregulation of miR-361-3p induced apoptosis and inhibited the proliferation of MM cells through targeting TRAF6, suggesting that miR-361-3p might be a potential target for MM therapy.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.564-572
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• 2002

This article describes the ultrasonic range sensor for the recognition of the Indoor environment, especially utilizing the multiple reflection properties of the sonar usually ignored as disturbances or noises. In this paper, we endow the ultrasonic range sensor with the active motion using the stepping servomechanism in order to get the multiple reflections with environment objects. Environment features such as target type, distance and azimuth based on the scanned one frame data of that multiple reflection patterns are recognized simultaneously.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.1958-1969
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• 1996

This paper proposed a new approach to adaptive call admission control based on a neural network for multiple service classes with different quality of service (QoS) in the ATM-based Broadband Integrated Services Digital Networks. the proposed method extend Hiramatsu's neural network based "leaky pattern table" method for the single QoS[1, 2, 3] to deal with multiple services with different QoS by constructing multiple pattern tables based on each service's acceptance or rejection at the call set-up requests, and by simultaneously controlling each service's QoS according to the target QoS of the service and the trunk capacity. Computer simulation results on two service classes with different traffic characteristics and different cell loss rates as QoS, highlight good performance and effectiveness of the proposed call admission controller for multiple service classes.e classes.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.4
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• pp.167-175
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• 2006

This paper presents a method to segment semiconductor wafer ID on poor quality images. The method is based on multiple templates and normalized gray-level correlation (NGC) method. If the lighting condition is not so good and hence, we can not control the image quality, target image to be inspected presents poor quality ID and it is not easy to identify and then recognize the ID characters. Conventional several method to segment the interesting ID regions fails on the bad quality images. In this paper, we propose a multiple template method, which uses combinational relation of multiple templates from model templates to match several characters of the inspection images. To find out the optimal solution of multiple template model in ID regions, we introduce newly-developed snake algorithm. Experimental results using images from real FA environment are presented.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2473-2475
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• 1998

In this paper, we implemented RS232C serial communication by the 2 wires(Data,GND), and multiple access, by the applying Collision Sensing Multiple Access(CSMA) Protocol. Multiple access is implemented by assigning a unique ID to each controller. The multiple access control operation starts by sending a command packet from a host to another host and the command packet is composed of ID bytes of source and target host computer, data bytes and the check sum, byte. In host computer, after sending command packet, the collision from loop back data. If collision is detected, it means a command packet was collided with another command packet for another host. The packet communication of the controller enables the multiple acces of the controller through the common serial data link. The application of this serial communication through CSMA protocol and the usage of two wires, have an effect on saving the wires and convenient of layout work.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1069-1080
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• 2016

TDOA(Time Difference Of Arrival)-based localization system such as the passive surveillance system performs the time synchronization between the receivers after separated installing multiple receivers to set the same clock for all receivers. And it estimates 2D(or 3D) location of the target by solving intersection of the multiple hyperbola(or hyperboloid) using TDOA. To perform time synchronization, one receiver must be set to the master, and it provide the reference data to compensate the clock of the rest of the slaves. The positioning accuracy of TDOA-based localization system is changed in accordance with the master that is selected among multiple receivers. So, the optimum receiver which is selected among multiple receivers must be set to master to get best performance in the considered deployment of receivers. In this paper, we propose a selection scheme of master receiver for time synchronization using DOP(Dilution Of Precision) which is based on location of the target and the multiple receivers. The proposed scheme has low complexity and short processing time, and it is easy to automate in the TDOA-based localization systems.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.82-89
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• 2012

This paper presents the intelligent tracking algorithm for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. Fuzzy c-mean clustering and predicted impact point are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by fuzzy c-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. The filtering process in a series of the algorithm which estimates the target value recognize the nonlinear maneuvering target as linear one because the filter recognize only remained noise by extracting acceleration from the positional error. After filtering process, we get the estimates target by compensating extracted acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. To maximize the effectiveness of the proposed system, we construct the multiple model structure. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.2
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• pp.1-13
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• 2017

In This Paper, we find the Target Candidate Region and the Location of the Candidate Region by Performing the Morphological Difference Calculation and Pixel Labeling for Robust Small Target Detection in Infrared Image with low SNR. Conventional Target Detection Methods based on Morphology Algorithms are low in Detection Accuracy due to their Vulnerability to Clutter in Infrared Images. To Address the Problem, Target Signal Enhancement and Background Clutter Suppression are Achieved Simultaneously by Combining Moravec Algorithm and LCM (Local Contrast Measure) Algorithm to Classify the Target and Noise in the Candidate Region. In Addition, the Proposed Algorithm can Efficiently Detect Multiple Targets by Solving the Problem of Limited Detection of a Single Target in the Target Detection method using the Morphology Operation and the Gaussian Distance Function Which were Developed for Real time Target Detection.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.978-983
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• 2010

Acoustic target classification in wireless sensor network is important research at environmental surveillance, invasion surveillance, multiple target separation. General sensor node signal processing methods concentrated on received signal energy based target detection and received raw signal compression. The former is not suited to target classification because of almost every target information are lost except target energy. The latter bring down life-time of sensor node owing to high computational complexity and transmission energy. In this paper, we introduce an feature extraction algorithm for acoustic target classification in wireless sensor network which has time and frequency information. The proposed method extracts time information and de-noised target classification information using wavelet decomposition step. This method reduces communication energy by 28% of original signal and computational complexity.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.580-586
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• 2023

AESA radar is able to instantaneously and adaptively position and control the beam, and this enables to greatly improve multi-target tracking capability with high accuracy in comparison to traditional mechanically-scanned radar system. This paper is primarily concerned with the development of an efficient methodology for multi-target managenent with the context of multi-target environment employing AESA radar. In this paper, targets are stratified into two principal categories: currently displayed targets and non-display targets, predicated upon their relative priority. Displayed targets are subsequently stratified into TOI (target of interest), HPT (high priority target), and SAT (situational awareness target), based on the requisite levels of tracking accuracy. It also suggests rules for determining target priority management, especially in air-to-air mode including interleaved mode. This proposed approach was tested and validated in a SIL (system integration lab) environment, applying it to AESA radars mounted on aircraft.