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Dive into the research topics where Beomju Shin is active.

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Featured researches published by Beomju Shin.


IEEE Sensors Journal | 2016

Motion Recognition-Based 3D Pedestrian Navigation System Using Smartphone

Beomju Shin; Chulki Kim; Jae Hun Kim; Seok Lee; Changdon Kee; Hyoung Seok Kim; Taikjin Lee

A motion recognition-based 3D pedestrian navigation system that employs a smartphone is presented. In existing inertial measurement unit (IMU)-based pedestrian dead-reckoning (PDR) systems, sensor axes are fixed regardless of user motion, because the IMU is mounted on the shoes or helmet. On the other hand, the sensor axes of a smartphone are changed according to the walking motion of the user, because the smartphone is usually carried by hand or kept in the pocket. Therefore, the conventional PDR method cannot apply to the smartphone-based PDR system. To overcome this limitation, the walking status is detected using a motion recognition algorithm with sensor measurements from the smartphone. Then, different PDR algorithms are applied according to the recognized pattern of the pedestrian motion. The height information of the pedestrian is also estimated using the on-board barometric pressure sensor of the smartphone. The 3D position, which consists of the 2D position calculated by the PDR and the height information, is provided to the pedestrian. The proposed system has several advantages in terms of cost and accessibility. It requires no additional peripheral devices except for the smartphone, because smartphones are equipped with all the necessary sensors, such as an accelerometer, magnetometer, gyroscope, and barometric pressure sensor. This paper implements the proposed system as an android-based application. The experimental results demonstrate the performance of the proposed system and reveal a high positioning accuracy.


international midwest symposium on circuits and systems | 2011

Interference compensation technique for multilevel flash memory

Myeongwoon Jeon; Kyungchul Kim; Beomju Shin; Jungwoo Lee

Multilevel cell flash memory devices are gaining popularity because it can increase the memory capacity by storing two or more bits to a single cell. However, when the number of levels of a cell increases, the inter-cell interference which shifts cell (threshold) voltage becomes more critical. Thereare two approaches to alleviate the errors caused by the voltage shift. One is the error correcting codes, and the other is the signal processing methods. We focus on signal processing methods to reduce the cell to cell interference which causes the voltage shift, and propose algorithms which reduce the voltage shift effects by classfying and compensating erratic cells. The simulation results show that the proposed algorithms are effective for interference reduction.


Journal of Sensor Science and Technology | 2014

Vapor Detection of ssDNA Decorated Graphene Transistor

Youngmo Jung; Young Jun Kim; Hi Gue Moon; Soo Min Kim; Beomju Shin; Joo Song Lee; Minah Seo; Taikjin Lee; Jae-Hun Kim; Seong Chan Jun; Seok Lee; Chulki Kim

Abstract We report a way to improve the ability of graphene to operate as a gas sensor by applying single stranded deoxyribonucleic acid(DNA). The sensitivity and recovery of the DNA-graphene sensor depending on the different DNA sequences are analyzed. The dif-ferent sensor responses to reactive chemical vapors are demonstrated in the time domain. Because of the chemical gating effect of thedeposited DNA, the resulting devices show complete and rapid recovery to baseline unlike the bare graphene at room temperature. Theapplication of the pattern recognition technique can increase the potential of DNA-graphene sensors as a chemical vapor classifier.Keywords: Gas sensors, Graphene, DNA, NO 2 , NH 3 , Sensitivity, Recovery 1. 서론 그래핀은 뛰어난 전기역학적 물질특성 및 균일한 표면 특성으로 인해 많은 학문적 관심을 받은 물질이다. 2차원 탄소 원자격자의 반복 구조체로 이루어진 그래핀은 고유의 에너지 밴드구조로 인하여 탄소 원자 부근에서 전자가 에너지 손실 없이 이동하는 것이 가능하며, 전하 이동도(mobility)가 높아 미세한 전기적 신호 검출에 유리하다[1]. 또한 그래핀을 대면적으로 성장시키고 이를 원하는 지지체(substrate)상에 전사하기 위한 다양한 연구가 진행되어, 균일한 표면 특성을 가지는 그래핀을 얻는것이 가능해졌다[2].이러한 특성으로 인하여 그래핀을 센서로서 적용하기 위한 많은 연구가 진행되었다. 많은 연구 분야 중에서, 현재 주목 받고있는 분야 중 하나가 그래핀을 이용한 가스 검출 연구 분야이다. 선행 연구에서, 팽창 흑연(HOPG)의 기계적 박리법(mechanicalexfoliation) 을 이용한 그래핀 가스 센싱에 대한 연구 결과가 발표되었으며[3], 이후 화학증기 증착법(chemical vapor deposition)을 이용한 그래핀 및 산화 그래핀(graphene oxide)을 이용한 가스 센서에 대한 연구 결과가 발표되었다[4,5].최근에는 기존의 그래핀만을 이용한 센서 연구에서, 그래핀과다양한 바이오 물질의 적용을 통해 그래핀의 전기적 역학적 특성이 개량된 센서에 대한 연구가 진행되고 있다[6]. 상기 언급한 대로, 그래핀은 2차원에서 균일한 표면 특성을 지니고 있으며, 표면에 존재하는 sp2 오비탈 구조체와 결합하여 바이오 물질을 고정화할 수 있다. 또한 그래핀 표면에 작용기(functionalgroup)를 활성화하여 이를 통해 선택적 결합을 유도하는 것도가능하다[7]. 이를 통하여 순수 그래핀이 가지는 전기역학적 특성을 보완 및 진보시킨 센서 제작이 가능하다.본 논문에서는 Single stranded Deoxyribonucleic acid(ssDNA)을 그래핀 표면에 결합시킨 그래핀/DNA 센서 거동에대한 연구 결과를 제시한다. Chemical vapor deposition(CVD)에 의해 성장된 그래핀을 이용하여 2×2 배열을 지니는 그래핀센서를 제작하였으며, 이를 통하여 NO


Proceedings of the 27th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2014) | 2014

A Step Length Estimation Based on Motion Recognition and Adaptive Gait Cognition Using a Smartphone

Jung Ho Lee; Beomju Shin; Seok Lee; Jin Woo Park; Jae-Hun Kim; Chulki Kim; Taikjin Lee


Etri Journal | 2014

Hybrid Model–Based Motion Recognition for Smartphone Users

Beomju Shin; Chulki Kim; Jae Hun Kim; Seok Lee; Changdon Kee; Taikjin Lee


Proceedings of the 25th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS 2012) | 2012

Motion-Awareness 3D PDR System in GPS-Denied Environment using Smartphone

Beomju Shin; Jung Ho Lee; Jae Hun Kim; Chulki Kim; Seok Lee; Young Tai Byun; Doohee Yun; Taikjin Lee


Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2017) | 2017

Localization in Urban Canyon: Machine Learning based Localization Using LTE or LoRa Signal for ‘GNSS-denied’ Areas

Boseon Yu; Beomju Shin; Jungho Lee; Seoho Lee; Taikjin Lee


Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2017) | 2017

WiFi Based Robust Positioning System in Large Scale and Weak Signal Environment

Beomju Shin; Boseon Yu; Jaewon Bang; Changdon Kee; Taikjin Lee


Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2017) | 2017

WiFi and PDR Based Robust SLAM Implementation using Surface Correlation

Beomju Shin; Boseon Yu; Jaewon Bang; Changdon Kee; Taikjin Lee


Proceedings of the 2017 International Technical Meeting of The Institute of Navigation | 2017

Performance Evaluation of LQG based Optimal GNSS Tracking Loop using Non-linear Measurements

Sanghoon Jeon; Minhuck Park; Beomju Shin; Changdon Kee; Chongwon Kim; Hyoungmin So; Jaegyu Jang; Ki Hoon Lee; Ki-Won Song

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Taikjin Lee

Seoul National University

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Changdon Kee

Seoul National University

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Chulki Kim

Korea Institute of Science and Technology

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Seok Lee

Catholic University of Korea

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Jae Hun Kim

Korea Institute of Science and Technology

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Jungwoo Lee

Seoul National University

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Kyungchul Kim

Seoul National University

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Myeongwoon Jeon

Seoul National University

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