• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.6
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• pp.974-978
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• 2011

The beam-matter interaction with various coating effects has received continued attention in the high power laser community. Previous works suggest that coatings promote target damage when compared to beaming on uncoated surface. Three types of paint coatings(Acrylic urethane, Silicone alkyd and Stealth blend) and a water coat on metals(Al, Ti and STS) are irradiated with a $CO_2$ laser. Both strain and temperature measurements are provided for assessing the instantaneous response characteristics of each coating on different metals. A selective combination of surface coats with metals has proven effective in either preventing or enhancing damage, both thermal and mechanical, associated with focused beaming on a target.

• Proceedings of the Korean Vacuum Society Conference
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• 2000.02a
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• pp.155-155
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• 2000

Adsorption of alkali metals on a silicon surface has attracted much attention due to its importance in metal-semiconductor interface technology, In particular, the bonding nature of alkali metal to silicon substrate has been a focus of fundamental research efforts. We examined the adsorbed layer of Cs on a Si(111)-(7$\times$) surface by reactive ion scattering (RIS) of hyperthermal Cs+ beams. RIS from a Cs-adsorbed surface gives rise to Cs, representing pickup of surface Cs by Cs projectile. The Cs intensity is proportional to surface coverage of Cs at a high substrate temperature (473 K), while it varies anomalously with Cs coverage at low temperatures (130-170 K). This observation indicates that RIS selectively detects metallic Cs on surface, but discriminates ionic Cs. Transition from ionic to metallic Cs adlayer is driven by thermal diffusion of Cs and their clustering process.

• Molecules and Cells
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• v.42 no.5
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• pp.386-396
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• 2019

Labeling of a protein with a specific dye or tag at defined positions is a critical step in tracing the subtle behavior of the protein and assessing its cellular function. Over the last decade, many strategies have been developed to achieve selective labeling of proteins in living cells. In particular, the site-specific unnatural amino acid (UAA) incorporation technique has gained increasing attention since it enables attachment of various organic probes to a specific position of a protein in a more precise way. In this review, we describe how the UAA incorporation technique has expanded our ability to achieve site-specific labeling and visualization of target proteins for functional analyses in live cells.

• Journal of Sensor Science and Technology
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• v.32 no.1
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• pp.1-9
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• 2023

Recently, the digital healthcare technologies including non-invasive diagnostics based on Internet of Things (IOT) are getting attention. Human exhaled breath contains a variety of volatile organic compounds (VOCs), which can provide information of malfunctions of the body and presence of a specific disease. Detection of VOCs in exhaled breath using gas sensors are easy to use, safe, and cost-effective. However, accurate diagnosis of diseases is challenging because changes in concentration of VOCs are extremely small and lots of body factors directly or indirectly influence to the conditions. To overcome the limitations, highly selective nanosensors and artificial intelligent electronic nose (E-nose) systems have been mainly researched in recent decades. This review provides brief reviews of the recent studies for diabetes and lung cancer diagnosis using nanosensors and E-nose systems.

• Annual Conference of KIPS
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• 2011.11a
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• pp.314-317
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• 2011

본 논문은 상향식 현저함 모델을 이용하여 입력 영상으로부터 시각적 주의를 갖는 영역들을 자동으로 검출하는 방법을 제안한다. 제안한 방법에서는 인간의 시각 시스템과 같이 사전 지식 없이 시각정보의 공간적인 분포에 근거하여 장면을 해석하는 상향식 현저함 모델 방법을 입력 영상에 적용하여 관심 물체 영역을 검출하는 연구이다. 상향식 현저함 방법은 Treisman의 세부특징이론 연구에서 제시한 바와 같이 시각적 주의를 갖는 영역은 시각정보의 현격한 대비차이를 가지는 영역으로 집중되어 배경에서 관심영역을 구분할 수 있다. 입력 영상에서 현저함 모델을 통해 3차원 현저함 맵을 생성한다. 그리고 생성된 현저함 맵으로부터 실제 관심영역들을 검출하기 위해 제안한 방법에서는 적응적 임계치 방법을 적용하여 관심영역을 검출한다. 제안한 방법을 관심영역 분할에 적용한 결과, 영역 분할 정확도 및 정밀도가 약 88%와 89%로 제시되어 관심 영상분할 시스템에 적용이 가능함을 알 수 있다.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.193-202
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• 2022

Semi-supervised learning has gained significant attention in recent applications. In this article, we provide a selective overview of popular semi-supervised methods and then propose a simple but effective algorithm for semi-supervised classification using support vector machines (SVM), one of the most popular binary classifiers in a machine learning community. The idea is simple as follows. First, we apply the dimension reduction to the unlabeled observations and cluster them to assign labels on the reduced space. SVM is then employed to the combined set of labeled and unlabeled observations to construct a classification rule. The use of SVM enables us to extend it to the nonlinear counterpart via kernel trick. Our numerical experiments under various scenarios demonstrate that the proposed method is promising in semi-supervised classification.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.4
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• pp.451-456
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• 2024

Organic photovoltaic (OPV) devices have attracted attention due to their high efficiency and simple manufacturing process. Applying an overlayer to OPV devices is one way to improve their performance because it can improve charge extraction and suppress vertical phase separation. In addition, dichloromethane (DCM) was used as an orthogonal solvent to minimize the effect on other layers. However, an coating problems due to the use of DCM were found, which affects surface morphology as rough or peeling. Additional research efforts are needed to solve these problems, and optimal results are expected to be obtained by utilizing various buffer layers or selective organic solvents.

• Microbiology and Biotechnology Letters
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• v.52 no.3
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• pp.233-254
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• 2024

The microorganisms that live under extreme conditions on Earth are known as extremophiles. They possess an extraordinary capability to endure extreme conditions, including salinity, temperature variations, pH, desiccation, and nutrient scarcity, among others. These organisms, including a vast array of bacteria, eukarya, and archaea, have evolved specialized structural and functional adaptations that make them capable of thriving in extremely selective environments in such a way that they showcase remarkable adaptations that push the limits of what we consider habitable. This capability results in valuable compounds with great potential for developing novel pharmaceuticals and biotechnological innovations. The present review paper aims to summarize current knowledge on the diversity of extremophilic microorganisms and the adaptive strategies employed to face such a range of extreme conditions. Particular attention will be given to temperature, salinity, pH, and desiccation adaptation. The review also highlights their potential applications, specifically focusing on pharmaceutical and biotechnological applications.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.115-122
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• 2016

This paper proposes a system to detect driver's cognitive state by internal and external information of vehicle. The proposed system can measure driver's eye gaze. This is done by concept of information delivery and mutual information measure. For this study, we set up two web-cameras at vehicles to obtain visual information of the driver and front of the vehicle. We propose Gestalt principle based selective attention model to define information quantity of road scene. The saliency map based on gestalt principle is prominently represented by stimulus such as traffic signals. The proposed system assumes driver's cognitive resource allocation on the front scene by gaze analysis and head pose direction information. Then we use several feature algorithms for detecting driver's characteristics in real time. Modified census transform (MCT) based Adaboost is used to detect driver's face and its component whereas POSIT algorithms are used for eye detection and 3D head pose estimation. Experimental results show that the proposed system works well in real environment and confirm its usability.

• Korean Journal of Biological Psychiatry
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• v.17 no.2
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• pp.79-85
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• 2010

Objectives : Trauma patients have attentional bias which enforces traumatic memories and causes cognitive errors. Understanding of such selective attention may explain many aspects of the posttraumatic stress disorder(PTSD) symptoms. Methods : We used the rapid serial visual presentation(RSVP) method to verify attentional blink in burn patients with PTSD. International affective picture system(IAPS) was used as stimuli and distracters. In the 'neutral test', patients have been presented series of pictures with human face picture as target stimuli. Each picture had 100ms interval. However the distance between target facial pictures was randomized and recognition of second facial picture accuracy was measured. In the 'stress test', the first target was stress picture which arouses patient emotions instead of the facial picture. Neutral and Stress tests were done with seven PTSD patients and 20 controls. In '85ms test' the interval was reduced to 85ms. The accuracy of recognition of second target facial picture was rated in all three tests. Eighty-five ms study was done with eighteen PTSD patients. Results : Attentional blinks were observed in 100-400ms of RSVP. PTSD patients showed increased recognition rate in the 'stress test' compared with the 'neutral test'. When presentation interval was decreased to 85 ms, PTSD patient showed decrease of attentional blink effect when target facial picture interval was 170ms. Conclusion : We found attentional blink effect could be affected by stress stimulus in burn patients. And attentional blink may be affected by stimulus interval and the character of stimulus. There may be some other specific mechanism related with selective attention in attentional blink especially with facial picture processing.