Jae-Ho Choi
포항공과대학교 공과대학 · 공학
Jae-Ho Choi 교수의 연구실은 나노구조 재료와 광학적 제어 기반의 스마트 소재 개발을 핵심으로 하며, 특히 유기 반도체 페로브스카이트를 활용한 저전압 다중 수준 저항성 스위칭 소자와, 자연에서 영감을 받은 초소수성/초오일포비아 표면 구조를 설계합니다. 또한, 레이더 기반 사람 수 세기 및 광학적 스위치링 구조를 활용한 정보 암호화 기술 등, 응용 기반의 혁신적 소자 설계에 주력하고 있습니다. 특히 광학적 제어를 통한 나노재료의 구조 형상 제어와, 딥러닝 기반 신호 처리 기법을 융합한 지능형 센서 기술 개발이 두드러집니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
Organolead halide perovskites are used for low-operating-voltage multilevel resistive switching. Ag/CH3 NH3 PbI3 /Pt cells exhibit electroforming-free resistive switching at an electric field of 3.25 × 10(3) V cm(-1) for four distinguishable ON-state resistance levels. The migration of iodine interstitials and vacancies with low activation energies is responsible for the low-electric-field resistive switching via filament formation and annihilation.
Springtails, insects which breathe through their skins, possess mushroom-shaped nanostructures. As doubly re-entrant geometry in the mushroom head enhances the resistance against liquid invasion, the springtails have robust, liquid-free omniphobic skins. Although omniphobic surfaces are promising for various applications, it remains an important challenge to mimic the structural feature of springtails. This paper presents a pragmatic method to create doubly re-entrant nanostructures and robust s
Conventional radar-based people counting systems are designed mainly for dense spatial distributions in a small region of interest (ROI). Therefore, a system with only conventional energy-based features, which are effective for a small ROI with a limited spatial distribution of individuals, generally fails to cope with the diverse and complex spatial distributions that arise from the freer movements of individuals as the ROI widens. To address this problem, a novel approach that achieves robust
Abstract Structural colors of 2D gratings are iridescent, color‐tunable, and never fade, which renders them appealing for anti‐counterfeiting applications. However, for advanced security, it still remains a challenge to completely hide the encrypted color patterns and reveal them on demand. In this work, a water‐responsive photonic grating consisting of a micropillar array and a hydrogel overcoat with a similar refractive index, termed “hydrocipher”, is presented. The joint effect of stimuli‐rev
Anisotropic movement of azobenzene materials (i.e., azobenzene molecules incorporated in polymer, glass, or supramolecules) has provided significant opportunities for the fabrication of micro/nanoarchitectures. The examples include circular holes, line gaps, ellipsoidal holes, and nanofunnels. However, all of the previous studies have only focused on the lateral directional movement for the structural shaping of azobenzene materials. Herein, we propose structural shaping based on a vertical dire
With the development of deep learning (DL) frameworks in the field of pattern recognition, DL-based algorithms have outperformed handcrafted feature (HF)-based ones in various applications. However, there still exist several challenges in applying the DL framework to a radar-based people counting (RPC) task: The powerful representation capacity of a deep neural network (DNN) learns not only the desired human-induced components but also unwanted nuisance factors, and available data for RPC is usu
Synthetic aperture radar (SAR) systems, which operate under a slant-viewing geometry, inevitably entail shadow regions in the resulting radar image. Such shadow profiles contain backprojected signatures of an object’s configuration as with target profiles; however, they are rarely utilized in current SAR-based recognition techniques. A major challenge in leveraging shadow information together lies in the intrinsic limitation of current single-pathway approaches, in which the target and shadow ca
In this study, a novel radar-based people counting (PC) method is presented using the deep learning (DL) approach. The DL algorithm is a great tool that enables the automatic formation of the optimal features; however, it must be utilized carefully, considering the domain knowledge to prevent the concerns of learning unnecessary information, followed by overfitting. To address the problem and successfully apply the DL framework to the radar-based PC, we propose three novel solutions. First, we e
<div class="htmlview paragraph">The numerical optimization techniques coupled with a three-dimensional Navier-Stokes solver have been developed to design an automotive cooling fan. The conjugate gradient method is used to look for the search direction and the golden section method is used for the one dimensional search. Concerning the constraints, exterior penalty functions are employed. In the applications of this numerical optimization technique to the design of an automotive cooling fan
Radar-based people counting (RPC) systems, which perceive their surroundings through wireless reflections from radar, can provide crowd information free from privacy invasion and illumination problems. Current RPC approaches leverage a deep supervised learning framework to classify the number of individuals from complicated radar data, based on a labeled set of signals. However, they have a critical limitation in terms of practicality in that even a marginal change in the surrounding environment
Directional photofluidization of azobenzene materials has provided unprecedented opportunities for the structural reconfiguration of circular holes, line gaps, ellipsoidal holes, and nanofunnel-shaped micro/nanoarchitectures. However, all the reconfigured structures have a parabolic or round wall due to the tendency of the photofluidized azobenezene materials to minimize the surface area, which limits their use as a reconfigurable etch-mask for the lithography process. In this work, a simple met
The noncontact respiration rate measurement (nRRM) method allows a system to monitor the breathing patterns of an individual without physical contact, which is crucial for regular health monitoring. Current nRRM approaches primarily depend on detecting minor variations in RGB profiles reflected from a camera to remotely extract respiration signals. However, these methods require continuous pixel-level tracking, which restricts their use on individuals in quasi-stationary sitting positions. To ad
Remote physiology, which involves monitoring vital signs without the need for physical contact, has great potential for various applications. Current remote physiology methods rely only on a single camera or radio frequency (RF) sensor to capture the microscopic signatures from vital movements. However, our study shows that fusing deep RGB and RF features from both sensor streams can further improve performance. Because these multimodal features are defined in distinct dimensions and have varyin