• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2799-2805
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• 2024

Energy-resolved neutron imaging is an effective way to investigate the internal structure and residual stress of materials. Different sample sizes have varying requirements for the detector's imaging field of view (FOV) and spatial resolution. Therefore, a dual-mode energy-resolved neutron imaging detector was developed, which mainly consisted of a neutron scintillator screen, a mirror, imaging lenses, and a time-stamping optical fast camera. This detector could operate in a large FOV mode or a high spatial resolution mode. To evaluate the performance of the detector, the neutron wavelength spectra and the multiple spatial resolution tests were conducted at CSNS. The results demonstrated that the detector accurately measured the neutron wavelength spectra selected by a bandwidth chopper. The best spatial resolution was about 20 ㎛ in high spatial resolution mode after event reconstruction, and a FOV of 45.0 mm × 45.0 mm was obtained in large FOV mode. The feasibility was validated to change the spatial resolution and FOV by replacing the scintillator screen and adjusting the lens magnification.

• Nuclear Engineering and Technology
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• v.53 no.6
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• pp.1942-1946
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• 2021

Gadolinium oxysulfide (GOS) is regarded as a novel scintillator for the realization of ultra-high spatial resolution in neutron imaging. Monte Carlo simulations of GOS scintillator show that the capability of its spatial resolution is towards the micron level. Through the time-of-flight method, the light output of a GOS scintillator was measured to be 217 photons per captured neutron, ~100 times lower than that of a ZnS/LiF:Ag scintillator. A detector prototype has been developed to evaluate the imaging solution with the GOS scintillator by neutron beam tests. The measured spatial resolution is ~36 ㎛ (28 line pairs/mm) at the modulation transfer function (MTF) of 10%, mainly limited by the low experimental collimation ratio of the beamline. The weak light output of the GOS scintillator requires an enormous increase in the neutron flux to reduce the exposure time for practical applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1462-1470
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• 2013

This paper proposes an SWAD-KNH(Sybil & Wormhole Attack Detection using Key, Neighbor list and Hop count) technique which consists of an SWAD(Sybil & Wormhole Attack Detection) module detecting an Worm attack and a KGDC(Key Generation and Distribution based on Cluster) module generating and an sense node key and a Group key by the cluster and distributing them. The KGDC module generates a group key and an sense node key by using an ECDH algorithm, a hash function, and a key-chain technique and distributes them safely. An SWAD module strengthens the detection of an Sybil attack by accomplishing 2-step key acknowledgement procedure and detects a Wormhole attack by using the number of the common neighbor nodes and hop counts of an source and destination node. As the result of the SWAD-KNH technique shows an Sybil attack detection rate is 91.2% and its average FPR 3.82%, a Wormhole attack detection rate is 90%, and its average FPR 4.64%, Sybil and wormhole attack detection rate and its reliability are improved.

• Bulletin of the Korean Chemical Society
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• v.35 no.8
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• pp.2400-2402
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• 2014

Cu (II) detection is of great importance owing to its significant function in various biological processes. In this report, we developed a novel coumarin-based chemosensor bearing the salicylaldimine unit (2) for $Cu^{2+}$ selective detection. The results from fluorescence spectra demonstrated that the sensor could selectively recognize $Cu^{2+}$ over other metal cations and the detection limit is as low as $0.2{\mu}M$. Moreover, the confocal fluorescence imaging in HepG2 cells illustrated its potential for biological applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2230-2252
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• 2024

Advances in deep learning technology have enabled the generation of more realistic deepfakes, which not only endanger individuals' identities but also exploit vulnerabilities in face recognition systems. The majority of existing deepfake detection methods have primarily focused on RGB-based analysis, offering unreliable performance in terms of detection accuracy and time. To address the issue, a grayscale-based deepfake detection method has recently been proposed. This method significantly reduces detection time while providing comparable accuracy to RGB-based methods. However, despite its significant effectiveness, the "key components" that directly affect the performance of grayscale-based deepfake detection have not been systematically analyzed. In this paper, we target three key components: RGB-to-grayscale conversion method, brightness level in grayscale, and resolution level in grayscale. To analyze their impacts on the performance of grayscale-based deepfake detection, we conducted comprehensive evaluations, including component-wise analysis and comparative analysis using real-world datasets. For each key component, we quantitatively analyzed its characteristics' performance and identified differences between them. Moreover, we successfully verified the effectiveness of an optimal combination of the key components by comparing it with existing deepfake detection methods.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.38-43
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• 2001

This Paper suggests a new feature for shot detection, using the proposed robust feature from the DC image constructed by DCT DC coefficients in the MPEG video stream, and proposes the characterizing value that reflects the characteristic of kind of video (movie, drama, news, music video etc.). The key frames are pulled out from many frames by using the local minima and maxima of differential of the value. After original frame(not do image) are reconstructed for key frame, indexing process is performed through computing parameters. Key frames that are similar to user's query image are retrieved through computing parameters. It is proved that the proposed methods are better than conventional method from experiments. The retrieval accuracy rate is so high in experiments.

• BMB Reports
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• v.39 no.3
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• pp.247-252
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• 2006

A rapid method for the detection of Hepatitis E Virus (HEV) was developed by utilizing nano-gold labeled oligonucleotide probes, silver stain enhancement and the microarray technique. The 5'-end -$NH_2$ modified oligonucleotide probes were immobilized on the surface of the chip base as the capture probe. The detection probe was made of the 3'-end -SH modified oligonucleotide probe and nano-gold colloid. The optimal concentrations of these two probes were determined. To test the detection sensitivity and specificity of this technique, a conservative fragment of the virus RNA was amplified by the RT-PCR/PCR one step amplification. The cDNA was hybridized with the capture probes and the detection probes on microarray. The detection signal was amplified by silver stain enhancement and could be identified by naked eyes. 100 fM of amplicon could be detected out on the microarray. As the results, preparation of nano-gold was improved and faster. Development time also was shortened to 2 min. Thus, considering high efficiency, low cost, good specificity and high sensitivity, this technique is alternative for the detection of HEV.

• Food Science and Biotechnology
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• v.18 no.4
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• pp.823-832
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• 2009

In recent years, special concerns have been raised about the safety assessment of foods and food ingredients derived from genetically modified organisms (GMOs). A growing number of countries establish regulations and laws for GMOs in order to allow consumers an informed choice. In this case, a lot of methods have been developed for the detection of GMOs. However, the reproducibility among methods and laboratories is still a problem. Consequently, it is still in great demand for more effective methods. In comparison with the gel electrophoresis, the capillary electrophoresis (CE) technology has some unique advantages, such as high resolution efficiency and less time consumption. Therefore, some CE-based methods have been developed for the detection of GMOs in recent years. All kinds of CE detection methods, such as ultraviolet (UV), laser induced fluorescence (LIF), and chemiluminescence (CL) detection, have been used for GMOs detection. Microchip capillary electrophoresis (MCE) methods have also been used for GMOs detection and they have shown some unique advantages.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.11
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• pp.4377-4384
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• 2014

According to the World Health Organization (WHO), 1.37 million people died of lung cancer all around the world in 2008, occupying the first place in all cancer-related deaths. However, this number might be decreased if patients were detected earlier and treated appropriately. Unfortunately, traditional imaging techniques are not sufficiently satisfactory for early detection of lung cancer because of limitations. As one alternative, breath volatile organic compounds (VOCs) may reflect the biochemical status of the body and provide clues to some diseases including lung cancer at early stage. Early detection of lung cancer based on breath analysis is becoming more and more valued because it is non-invasive, sensitive, inexpensive and simple. In this review article, we analyze the limitations of traditional imaging techniques in the early detection of lung cancer, illustrate possible mechanisms of the production of VOCs in cancerous cells, present evidence that supports the detection of such disease using breath analysis, and summarize the advances in the study of E-noses based on gas sensitive sensors. In conclusion, the analysis of breath VOCs is a better choice for the early detection of lung cancer compared to imaging techniques. We recommend a more comprehensive technique that integrates the analysis of VOCs and non-VOCs in breath. In addition, VOCs in urine may also be a trend in research on the early detection of lung cancer.

• Structural Engineering and Mechanics
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• v.54 no.2
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• pp.379-392
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• 2015

A number of acceleration-based damage detection methods have been developed but they have not been widely applied in engineering practices because the acceleration response is insensitive to minor damage of civil structures. In this article, a damage detection approach using the long-gauge strain sensing technology and the principle component analysis technology is proposed. The Long gauge FBG sensor has its special merit for damage detection by measuring the averaged strain over a long-gauge length, and it can be connected each other to make a distributed sensor network for monitoring the large-scale civil infrastructure. A new damage index is defined by performing the principle component analyses of the long-gauge strains measured from the intact and damaged structures respectively. Advantages of the long gauge sensing and the principle component analysis technologies guarantee the effectiveness for structural damage localization. Examples of a simple supported beam and a steel stringer bridge have been investigated to illustrate the successful applications of the proposed method for structural damage detection.