• Journal of Electrochemical Science and Technology
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• 제7권4호
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• pp.286-292
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• 2016

Chemically amplified electrochemical detection, redox-active probe being amplified its electrochemical anodic current by a sacrificial electron donor presenting in solution, holds great potential for simple and quantitative bioanalytical analysis. Herein, we report the chemically amplified electrochemical analysis that drastically enhanced a detection of ferrocenemethanol (analyte) by ferrocyanide (chemical amplifier) on 4-nitrophenyl grafted glassy carbon electrodes at $60^{\circ}C$. The glassy carbon electrode grafted with a 4-nitrophenyl group using an electrochemical reduction suppressed the oxidation of ferrocyanide and thus enabled detection of ferrocenemethanol with excellent selectivity. The ferrocenemethanol was detected down to an nM range using a linear sweep voltammetry under kinetically optimized conditions. The detection limit was improved by decreasing the concentration of the ferrocyanide and increasing temperature.

• 한국의학물리학회지:의학물리
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• 제33권2호
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• pp.11-24
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• 2022

X-ray detection has widely been applied in medical diagnostics, security screening, nondestructive testing in the industry, etc. Medical X-ray imaging procedures require digital flat detectors operating with low doses to reduce radiation health risks. Recently, metal halide perovskites (MHPs) have shown great potential in high-performance X-ray detection because of their attractive properties, such as strong X-ray absorption, high mobility-lifetime product, tunable bandgap, low-temperature fabrication, near-unity photoluminescence quantum yields, and fast photoresponse. In this paper, we review and introduce the development status of new perovskite X-ray detectors and imaging, which have emerged as a new promising high-sensitivity X-ray detection technology. We discuss the latest progress and future perspective of MHP-based X-ray detection in medical imaging. Finally, we compare the conventional detection methods with quantum-enhanced detection, pointing out the challenges and perspectives for future research directions toward perovskite-based X-ray applications.

• 대한임베디드공학회논문지
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• 제18권5호
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• pp.225-231
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• 2023

With the recent surge in the autonomous driving market, the significance of lane detection technology has escalated. Lane detection plays a pivotal role in autonomous driving systems by identifying lanes to ensure safe vehicle operation. Traditional lane detection models rely on engineers manually extracting lane features from predefined environments. However, real-world road conditions present diverse challenges, hampering the engineers' ability to extract adaptable lane features, resulting in limited performance. Consequently, recent research has focused on developing deep learning based lane detection models to extract lane features directly from data. In this paper, we classify lane detection models into four categories: cluster-based, curve-based, information propagation-based, and anchor-based methods. We conduct an extensive analysis of the strengths and weaknesses of each approach, evaluate the model's performance on an embedded board, and assess their practicality and effectiveness. Based on our findings, we propose future research directions and potential enhancements.

• Computers and Concrete
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• 제32권6호
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• pp.615-623
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• 2023

Crack detection is an essential method to ensure the safety of dam concrete structures. Low-quality crack images of dam concrete structures limit the application of neural network methods in crack detection. This research proposes a modified attentional mechanism model to reduce the disturbance caused by uneven light, shadow, and water spots in crack images. Also, the focal loss function solves the small ratio of crack information. The dataset collects from the network, laboratory and actual inspection dataset of dam concrete structures. This research proposes a novel method for crack detection of dam concrete structures based on the U-Net neural network, namely AF-UNet. A mutual comparison of OTSU, Canny, region growing, DeepLab V3+, SegFormer, U-Net, and AF-UNet (proposed) verified the detection accuracy. A binocular camera detects cracks in the experimental scene. The smallest measurement width of the system is 0.27 mm. The potential goal is to achieve real-time detection and localization of cracks in dam concrete structures.

• JSTS:Journal of Semiconductor Technology and Science
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• 제13권4호
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• pp.395-401
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• 2013

In-situ optical emission spectroscopy (OES) is employed for leak detection in plasma etching system. A misprocessing is reported for significantly reduced silicon etch rate with chlorine gas, and OES is used as a supplementary sensor to analyze the gas phase species that reside in the process chamber. Potential cause of misprocessing reaches to chamber O-ring wear out, MFC leaks, and/or leak at gas delivery line, and experiments are performed to funnel down the potential of the cause. While monitoring the plasma chemistry of the process chamber using OES, the emission trace for nitrogen species is observed at the chlorine gas supply. No trace of nitrogen species is found in other than chlorine gas supply, and we found that the amount of chlorine gas is slightly fluctuating. We successfully found the root cause of the reported misprocessing which may jeopardize the quality of thin film processing. Based on a quantitative analysis of the amount of nitrogen observed in the chamber, we conclude that the source of the leak is the fitting of the chlorine mass flow controller with the amount of around 2-5 sccm.

• 한국통신학회논문지
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• 제40권1호
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• pp.142-151
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• 2015

본 논문에서는 이동 카메라 환경에서 이동 및 이동 중 정지물체를 검출하기 위한 방법을 제안한다. 이동 중에 일시적으로 정지한 물체는 검출 결과의 응용관점에서 볼 때 이동물체의 검출만큼이나 중요한데, 기존의 이동물체 검출 방법들은 이들을 배경과 구분하지 못하는 한계를 갖는다. 이러한 문제를 해결하기 위해 제안하는 방법에서는 이동 가능성 큐, 위치 가능성 큐, 그리고 색 분포 유사성 큐를 정의하여 이동물체 검출 및 지속적인 추적에 이용한다. 그래프 컷 알고리즘은 세 개의 큐를 결합하여 시공간 영상분할을 수행함으로써 이동 및 이동 중 정지물체를 검출한다. 제안하는 방법은 이동물체 뿐 아니라 이동 중 정지물체에 대해서도 검출이 가능함을 실험을 통해 증명하였다.

• 한국소음진동공학회논문집
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• 제17권3호
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• pp.257-263
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• 2007

Detection of structural damage is an inverse problem in structural engineering. There are three main questions in the damage detection: existence, location and extent of the damage. In concept, the natural frequency and mode shapes of any structure must satisfy an eigenvalue problem. But, if a potential damage exists in a structure, an error resulting from the substitution of the refined analytical finite element model and measured modal data into the structural eigenvalue equation will occur, which is called the residual modal forces, and can be used as an indicator of potential damage in a structure. In this study, a useful damage detection method is proposed and compared with other two methods. Two degree-of-freedom system and Cantilever beam are used to demonstrate the approach. And the results of three introduced method are compared.

• IMMUNE NETWORK
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• 제24권2호
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• pp.12.1-12.17
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• 2024

Exosomes are double phospholipid membrane vesicles that are synthesized and secreted by a variety of cells, including T cells, B cells, dendritic cells, immune cells, are extracellular vesicles. Recent studies have revealed that exosomes can play a significant role in under both physiological and pathological conditions. They have been implicated in regulation of inflammatory responses, immune response, angiogenesis, tissue repair, and antioxidant activities, particularly in modulating immunity in autoimmune diseases (AIDs). Moreover, variations in the expression of exosome-related substances, such as miRNA and proteins, may not only offer valuable perspectives for the early warning, and prognostic assessment of various AIDs, but may also serve as novel markers for disease diagnosis. This article examines the impact of exosomes on the development of AIDs and explores their potential for therapeutic application.

• 한국컴퓨터정보학회논문지
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• 제29권3호
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• pp.127-136
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• 2024

본 연구는 Spark 클러스터 환경에서 대용량 로그를 분석하여 시스템 이상과의 연관성을 탐색한다. 로그를 활용한 이상 감지 연구는 증가하고 있으나, 클러스터의 다양한 컴포넌트의 로그를 충분히 활용하지 못하고 이상과 시스템의 연관성을 고려하지 않는다는 한계가 있다. 따라서 본 논문에서는 정상과 비정상 로그의 분포를 분석하고, 로그 템플릿의 출현 여부를 통해 이상 감지 가능성을 탐색한다. Hadoop과 Spark를 활용하여 정상과 비정상 로그 데이터를 생성하고, t-SNE와 K-means 클러스터링을 통해 비정상 상황에서의 로그 템플릿을 찾아 이상 현상을 파악한다. 결과적으로, 비정상 상황에서만 발생하는 고유한 로그 템플릿을 확인하며 이를 통해 이상 현상 감지의 가능성을 제시한다.

• 대한의생명과학회지
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• 제21권4호
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• pp.165-171
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• 2015

Microbial pathogens are responsible for most of the rapidly-spreading deadly infectious diseases against humans. Thus, there is an urgent need for efficient and rapid detection methods for infectious microorganisms. The detection methods should not only be targeted and specific, but they have to be encompassing of potential changes of the pathogen as it evolves and mutates quickly during an epidemic or pandemic. The existing diagnostics such as the antibody-based ELISA immunoassay and PCR methods are too selective and narrowly focused; they are insufficient to capture newly evolved mutant strains of the pathogen. Here, we introduce a fresh perspective on some new technologies, including aptamers and next generation sequencing for pathogen detection. These technologies are not in their infancy; they are reasonably mature and ready, and they hold great promise for unparalleled applications in pathogen detection.