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Specialized Sensors and System Modeling for Safety-critical Application
Jeong, Taikyeong Ted The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.3
Special purpose sensor design using MEMS (Micro-Electro-Mechanical Systems) technique is commonly used in Nondestructive Testing (NDT) research for the evaluation of existing structures and for the safety control and requirements. Various sensors and network have been developed for general infrastructures as well as safety-critical applications, e.g., aerospace, defense, and nuclear system, etc. In this paper, one of sensor technique using Fiber Bragg Gratings (FBG) and Finite Element Method (FEM) evaluation is discussed. The experimental setup and data collection technique is also demonstrated. The factors influencing test result and the advantages/limitations of this technique are also reviewed using various methods.
Specialized Sensors and System Modeling for Safety-critical Application
Taikyeong Ted. Jeong 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.3
Special purpose sensor design using MEMS (Micro-Electro-Mechanical Systems) technique is commonly used in Nondestructive Testing (NDT) research for the evaluation of existing structures and for the safety control and requirements. Various sensors and network have been developed for general infrastructures as well as safety-critical applications, e.g., aerospace, defense, and nuclear system, etc. In this paper, one of sensor technique using Fiber Bragg Gratings (FBG) and Finite Element Method (FEM) evaluation is discussed. The experimental setup and data collection technique is also demonstrated. The factors influencing test result and the advantages/limitations of this technique are also reviewed using various methods.
Simulation-based Design Verification for High-performance Computing System
Jeong Taikyeong T. Korea Multimedia Society 2005 멀티미디어학회논문지 Vol.8 No.12
This paper presents the knowledge and experience we obtained by employing multiprocessor systems as a computer simulation design verification to study high-performance computing system. This paper also describes a case study of symmetric multiprocessors (SMP) kernel on a 32 CPUs CC-NUMA architecture using an actual architecture. A small group of CPUs of CC-NUMA, high-performance computer system, is clustered into a processing node or cluster. By simulating the system design verification tools; we discussed SMP OS kernel on a CC-NUMA multiprocessor architecture performance which is $32\%$ of the total execution time and remote memory access latency is occupied $43\%$ of the OS time. In this paper, we demonstrated our simulation results for multiprocessor, high-performance computing system performance, using simulation-based design verification.
An Adaptive Steganography of Optical Image using Bit-Planes and Multi-channel Characteristics
강진석,Taikyeong T. Jeong 한국광학회 2008 Current Optics and Photonics Vol.12 No.3
We proposed an adaptive steganography of an optical image using bit-planes and multichannel characteristics. The experiment’s purpose was to compare the most popular methods used in optical steganography and to examine their advantages and disadvantages. In this paper we describe two digital methods: the first uses less significant bits (LSB) to encode hidden data, and in the other all blocks of n×n pixels are coded by using DCT (Digital Cosine Transformation), and two optical methods: double phase encoding and digital hologram watermarking with double binary phase encoding by using IFTA(Iterative Fourier Transform Algorithm) with phase quantization. Therefore, we investigated the complexity on bit plane and data, similarity insert information into bit planes. As a result, the proposed method increased the insertion capacity and improved the optical image quality as compared to fixing threshold and variable length method.
LEE, Sungju,REZAEI, Mehdi,JEONG, Taikyeong Tehran University of Medical Sciences 2018 Iranian journal of public health Vol.47 No.4
<P><B>Background:</B></P><P>The aim of this study was to investigate the correlation and interaction between the air pollution’s components with cardiopulmonary endurance of elderly people in eight regions by using a multi-modal and correlation analysis.</P><P><B>Methods:</B></P><P>The data of air pollution was collected in eight selected regions in 2013 to 2015. At the same time, total number of 880 male and female, older than 65 year-olds, were investigated based on the cardiopulmonary endurance measurement in the same regions. The correlation, interaction and multiple linear regressions was tested between the air pollution components in each region and cardiopulmonary endurance of elderly people, also between the air pollution components in each region and gender, respectively. In this case, the regression analysis for both hypotheses was conducted.</P><P><B>Results:</B></P><P>There was a correlation between the level of air pollution and cardiopulmonary endurance, especially for the carbon monoxide which has a strong effect, it was followed by the effect of sulfur dioxide and fine dust, meanwhile nitrogen dioxide seems not to be effective for this measurement test. Furthermore, it was highly unlikely that gender was a significant factor for the correlation between air pollution and cardiopulmonary endurance.</P><P><B>Conclusion:</B></P><P>The importance and correlation between air pollution and cardiopulmonary capacity is a critical determinant for the public health of a society, while at the same time having a serious impact on certain age groups. Provided that the factor of gender is highly unlikely to modify this impact, it is necessary to study the potential of other factors.</P>
A Capacitor-less Low Dropout Regulator for Enhanced Power Supply Rejection
Yun, Seong Jin,Kim, Jeong Seok,Jeong, Taikyeong Ted.,Kim, Yong Sin The Institute of Electronics and Information Engin 2015 IEIE Transactions on Smart Processing & Computing Vol.4 No.3
Various power supply noise sources in a system integrated circuit degrade the performance of a low dropout (LDO) regulator. In this paper, a capacitor-less low dropout regulator for enhanced power supply rejection is proposed to provide good power supply rejection (PSR) performance. The proposed scheme is implemented by an additional capacitor at a gate node of a pass transistor. Simulation results show that the PSR performance of the proposed LDO regulator depends on the capacitance value at the gate node of the pass transistor, that it can be maximized, and that it outperforms a conventional LDO regulator.
사용자 참여형 웨어러블 디바이스 데이터 전송 연계 및 딥러닝 대사증후군 예측 모델
이현식(Hyunsik Lee),이웅재(Woongjae Lee),정태경(Taikyeong Jeong) 한국산업정보학회 2020 한국산업정보학회논문지 Vol.25 No.6
본 논문은 최근 다양한 종류의 웨어러블 디바이스가 헬스케어 도메인에 급증하여 사용되고 있는 상황에서 최신 첨단 기술이 실제 메디컬 환경에서 개인의 질병예측이라는 관점을 바라본다. 사용자 참여형 웨어러블 디바이스를 통하여 임상 데이터와 유전자 데이터, 라이프 로그 데이터를 병합하여 데이터를 수집, 처리, 전송하는 과정을 걸쳐 딥뉴럴 네트워크의 환경에서 학습모델의 제시와 피드백 모델을 연결하는 과정을 제시한다. 이러한 첨단 의료 현장에서 일어나는 메디컬 IT의 임상시험 절차를 걸친 실제 현장의 경우 대사 증후군에 의한 특정 유전자가 질병에 미치는 영향을 측정과 더불어 임상 정보와 라이프 로그 데이터를 병합하여 서로 각기 다른 이종 데이터를 처리하면서 질병의 특이점을 확인하게 된다. 즉, 이종 데이터의 딥뉴럴 네트워크의 객관적 적합성과 확실성을 증빙하게 되고 이를 통한 실제 딥러닝 환경에서의 노이즈에 따른 성능 평가를 실시한다. 이를 통해 자동 인코더의 경우의 1,000 EPOCH당 변화하는 정확도와 예측치가 변수의 증가 값에 수차례 선형적으로 변화하는 현상을 증명하였다. This paper aims to look at the perspective that the latest cutting-edge technologies are predicting individual diseases in the actual medical environment in a situation where various types of wearable devices are rapidly increasing and used in the healthcare domain. Through the process of collecting, processing, and transmitting data by merging clinical data, genetic data, and life log data through a user-participating wearable device, it presents the process of connecting the learning model and the feedback model in the environment of the Deep Neural Network. In the case of the actual field that has undergone clinical trial procedures of medical IT occurring in such a high-tech medical field, the effect of a specific gene caused by metabolic syndrome on the disease is measured, and clinical information and life log data are merged to process different heterogeneous data. That is, it proves the objective suitability and certainty of the deep neural network of heterogeneous data, and through this, the performance evaluation according to the noise in the actual deep learning environment is performed. In the case of the automatic encoder, we proved that the accuracy and predicted value varying per 1,000 EPOCH are linearly changed several times with the increasing value of the variable.