• Bulletin of the Korean Chemical Society
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• v.35 no.8
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• pp.2423-2430
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• 2014

Nitrogen-doped short tubular carbons (N-STCs) with big inner diameter have been successfully synthesized via carbonization of polydopamine (PDA) wrapped halloysite nanotubes (HNTs). The obtained N-STCs have average length of $0.3{\mu}m$ with big inner diameter (50 nm), thin wall (2-3 nm) and large surface area ($776m^2g^{-1}$), and show excellent electrochemical properties. As an example in electrochemical applications, N-STCs were used to electrochemically detect hydrogen peroxide ($H_2O_2$) and glucose. The results showed that the N-STCs modified glassy carbon (N-STCs/GC) electrode had much better analytical performance (lower detection limit and wider linear range) compared to the acid-treated carbon nanotubes (AO-CNTs) based GC electrode. The unique structure endows N-STCs the enhanced electrochemical performance and promising applications in electrochemical sensing.

• Geomechanics and Engineering
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• v.25 no.4
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• pp.295-302
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• 2021

Cross-borehole electrical resistivity tomography (ERT) is an effective groundwater detection tool in geophysical investigations. In this paper, an artificial water injection test was conducted on a small clay sample, where the high-resolution cross-borehole ERT was used to investigate the moisture migration law over time. The moisture migration path can be two-dimensionally imaged based on the relationship between resistivity and saturation. The hydraulic conductivity was estimated, and the magnitude ranged from 10^-11 m/s to 10^-9 m/s according to the comparison between the simulation flow and the saturation distribution inferred from ERT. The results indicate that cross-borehole ERT could help determine the resistivity distribution of small size clay samples. Finally, the cross-borehole ERT technique has been applied to investigate the self-sealing characteristics of clay.

• Parasites, Hosts and Diseases
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• v.58 no.2
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• pp.181-184
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• 2020

Blastocystis, an enteric protist, has been reported to be an important cause of protozoal gastrointestinal manifestations in humans and animals worldwide. Animals harboring certain Blastocystis subtypes (STs) may serve as a potential source of human infection. However, information about the prevalence and genetic diversity of Blastocystis in alpacas is limited. In the present study, a total of 366 fecal samples from alpacas in Shanxi Province, northern China, were examined for Blastocystis by PCR amplification of the small subunit rRNA gene, followed by sequencing and phylogenetic analysis. The prevalence of Blastocystis in alpacas was 23.8%, and gender difference in the prevalence of Blastocystis was observed. The most predominant Blastocystis ST was ST10, followed by ST14 and ST5. The detection of ST5, a potentially zoonotic genotype, indicates that alpacas harboring ST5 could be a potential source of human infection with Blastocystis. These data provide new insight into the prevalence and genetic diversity of Blastocystis in alpacas.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.5
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• pp.225-230
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• 2015

In this paper, we propose an effective real-time visual loop closure detector, VILODE, which makes use of key frames and bag of visual words (BoW) based on SURF feature points. In order to determine whether the camera has re-visited one of the previously visited places, a loop closure detector has to compare an incoming new image with all previous images collected at every visited place. As the camera passes through new places or locations, the amount of images to be compared continues growing. For this reason, it is difficult for a visual loop closure detector to meet both real-time constraint and high detection accuracy. To address the problem, the proposed system adopts an effective key frame selection strategy which selects and compares only distinct meaningful ones from continuously incoming images during navigation, and so it can reduce greatly image comparisons for loop detection. Moreover, in order to improve detection accuracy and efficiency, the system represents each key frame image as a bag of visual words, and maintains indexes for them using DBoW database system. The experiments with TUM benchmark datasets demonstrates high performance of the proposed visual loop closure detector.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.4
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• pp.283-289
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• 2016

Islanding protection of a grid-connected photovoltaic (PV) inverter is a key function for standards compliance. Unintentional islanding results in safety hazards, reliability, and many other issues. Therefore, many anti-islanding schemes have been examined. However, existing anti-islanding schemes have poor power quality and non-detection zone issues. Moreover, most schemes have problems that deteriorate the performance of islanding detection under parallel operation. Therefore, this paper proposes a novel anti-islanding scheme that has negligible power quality degradation and has no non-detection zone and islanding detection under a parallel operation. Both simulation and experimental results validate the proposed scheme.

• The Journal of the Korean dental association
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• v.49 no.8
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• pp.461-471
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• 2011

The detection of carious lesions is a key point to apply appropriate preventive measures or operative treatment of dental caries. A laser fluorescence device DIAGNOdent$^{(R)}$ (KaVo, Biberach, Germany) has also been shown to be of additional clinical value in the detection of initial caries. This report focus on the DIAGNOdent$^{(R)}$ for caries detection. DIAGNOdent$^{(R)}$ irradiate visible red light at a wavelength of 655 nm to elicit near-infrared fluorescence from caries lesion. This device is known as a reproducible method for caries detection, with good sensitivity and specificity especially for caries detection on occlusal and accessible smooth surfaces. DIAGNOdent$^{(R)}$ tended to be more sensitive method of detecting occlusal dentinal caries, however, showed more false-positive diagnoses than the visual inspection. So Clinician should not use the device as a clinician's primary diagnostic method and it is recommended that the device should be used in the decision-making process in relation to the diagnosis of caries as a second opinion in cases of doubt after visual inspection. The trend of modern dentistry would be a preventive approach rather than invasive treatment of the disease. This is possible only with early detection and respective preventive measures, DIAGNOdent$^{(R)}$ can help the changes.

• Journal of Advanced Navigation Technology
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• v.6 no.3
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• pp.231-240
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• 2002

For a long time target maneuvers in tracking problem have been a difficult task to handle. In order to solve this problems. there have been various tracking techniques. In the development of a tracking filter for a maneuvering target, maneuver detection threshold plays a key role. However, no study of filter performance the varying maneuver detection threshold has been carried out so far. Instead, the maneuver detection have been chosen empirically. In this paper, the effect of detection threshold selection on the performance of the tracking filters was considered and the relationships between maneuvers and the detection threshold have been analyzed by simulation.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.192-198
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• 2020

The 3D point cloud is a key technology of object detection for virtual reality and augmented reality. In order to apply various areas of object detection, it is necessary to obtain 3D information and even color information more easily. In general, to generate a 3D point cloud, it is acquired using an expensive scanner device. However, 3D and characteristic information such as RGB and depth can be easily obtained in a mobile device. GNN (Graph Neural Network) can be used for object detection based on these characteristics. In this paper, we have generated RGB and RGBD by detecting basic information and characteristic information from the KITTI dataset, which is often used in 3D point cloud object detection. We have generated RGB-GNN with i-GNN, which is the most widely used LiDAR characteristic information, and color information characteristics that can be obtained from mobile devices. We compared and analyzed object detection accuracy using RGBD-GNN, which characterizes color and depth information.

• ETRI Journal
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• v.37 no.6
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• pp.1199-1210
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• 2015

Automatic emotion recognition based on facial cues, such as facial action units (AUs), has received huge attention in the last decade due to its wide variety of applications. Current computer-based automated two-phase facial emotion recognition procedures first detect AUs from input images and then infer target emotions from the detected AUs. However, more robust AU detection and AU-to-emotion mapping methods are required to deal with the error accumulation problem inherent in the multiphase scheme. Motivated by our key observation that a single AU detector does not perform equally well for all AUs, we propose a novel two-phase facial emotion recognition framework, where the presence of AUs is detected by group decisions of multiple AU detectors and a target emotion is inferred from the combined AU detection decisions. Our emotion recognition framework consists of three major components - multiple AU detection, AU detection fusion, and AU-to-emotion mapping. The experimental results on two real-world face databases demonstrate an improved performance over the previous two-phase method using a single AU detector in terms of both AU detection accuracy and correct emotion recognition rate.

• Journal of Microbiology and Biotechnology
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• v.24 no.3
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• pp.297-312
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• 2014

Food safety is increasingly becoming an important public health issue, as foodborne diseases present a widespread and growing public health problem in both developed and developing countries. The rapid and precise monitoring and detection of foodborne pathogens are some of the most effective ways to control and prevent human foodborne infections. Traditional microbiological detection and identification methods for foodborne pathogens are well known to be time consuming and laborious as they are increasingly being perceived as insufficient to meet the demands of rapid food testing. Recently, various kinds of rapid detection, identification, and monitoring methods have been developed for foodborne pathogens, including nucleic-acid-based methods, immunological methods, and biosensor-based methods, etc. This article reviews the principles, characteristics, and applications of recent rapid detection methods for foodborne pathogens.