• Annals of Laboratory Medicine
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• v.38 no.6
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• pp.569-577
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• 2018

Background: The increasing prevalence of drug-resistant tuberculosis (TB) infection represents a global public health emergency. We evaluated the usefulness of a newly developed multiplexed, bead-based bioassay (Quantamatrix Multiplexed Assay Platform [QMAP], QuantaMatrix, Seoul, Korea) to rapidly identify the Mycobacterium tuberculosis complex (MTBC) and detect rifampicin (RIF) and isoniazid (INH) resistance-associated mutations. Methods: A total of 200 clinical isolates from respiratory samples were used. Phenotypic anti-TB drug susceptibility testing (DST) results were compared with those of the QMAP system, reverse blot hybridization (REBA) MTB-MDR assay, and gene sequencing analysis. Results: Compared with the phenotypic DST results, the sensitivity and specificity of the QMAP system were 96.4% (106/110; 95% confidence interval [CI] 0.9072-0.9888) and 80.0% (72/90; 95% CI 0.7052-0.8705), respectively, for RIF resistance and 75.0% (108/144; 95% CI 0.6731-0.8139) and 96.4% (54/56; 95% CI 0.8718-0.9972), respectively, for INH resistance. The agreement rates between the QMAP system and REBA MTB-MDR assay for RIF and INH resistance detection were 97.6% (121/124; 95% CI 0.9282-0.9949) and 99.1% (109/110; 95% CI 0.9453-1.0000), respectively. Comparison between the QMAP system and gene sequencing analysis showed an overall agreement of 100% for RIF resistance (110/110; 95% CI 0.9711-1.0000) and INH resistance (124/124; 95% CI 0.9743-1.0000). Conclusions: The QMAP system may serve as a useful screening method for identifying and accurately discriminating MTBC from non-tuberculous mycobacteria, as well as determining RIF- and INH-resistant MTB strains.

• Journal of Information Technology Services
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• v.12 no.4
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• pp.435-447
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• 2013

If we use a smartphone to analyze and detect falling, it is a huge advantage that the person with a sensor attached to one's body is free from awareness of difference and limitation of space, unlike attaching sensors on certain fixed areas. In this paper, we suggested effective posture analysis of smartphone users, and fall detecting system. Suggested algorithm enables to detect falling accurately by using the fact that instantaneous change of acceleration sensor is different according to user's posture. Since mobile applications working on smart phones are low in compatibility according to mobile platforms, it is a constraint that new development is needed which is suitable for sensor equipment's characteristics. In this paper, we suggested posture analysis algorithm using smartphones to solve the problems related to user's inconvenience and limitation of development according to sensor equipment's characteristics. Also, we developed fall detection system with the suggested algorithm, using hybrid mobile application which is not limited to platform.

• Journal of Sensor Science and Technology
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• v.15 no.3
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• pp.158-163
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• 2006

This paper reports a novel immunoassay method using superparamagnetic nanoparticles and an enhanced magnetic field gradient for the detection of protein in a microfluidic device. We use superparamagnetic nanoparticles as a label and fluorescent polystyrene beads as a solid support. Based on this platform, magnetic force-based microfluidic immunoassay is successfully applied to analyze the concentration of IgG as model analytes. In addition, we present ferromagnetic microstructure connected with a permanent magnet to increase magnetic flux density gradient (dB/dx, ${\sim}10^{4}$ T/m), which makes limit of detection reduced. The detection limit is reduced to about 1 pg/mL.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.3
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• pp.280-284
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• 2011

The mass change during the molecular interaction between explosive specific bio-receptors and target molecules has been measured using quartz crystal microbalance(QCM), which has a mass change detection limit up to ~ng/$cm^2$. The environmental effect on the molecular interaction has been evaluated. In the liquid phase molecular interaction experiments, the high selectivity of the bio-receptor to DNT compared with toluene has been shown and the sensitivity for various concentrations of DNT has been demonstrated.

• Bulletin of the Korean Chemical Society
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• v.35 no.11
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• pp.3195-3198
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• 2014

An ultra-sensitive detection method for small molecules such as antibiotics was developed using ICP-MS with magnetic and $TiO_2$ nanoparticles. Since most of the antibiotics are too small to employ a sandwich-type extraction through an immunoreaction, a non-specific platform was employed, in which the target was extracted by magnetic separation, followed by tagging with $TiO_2$ nanoparticles of 11.2 nm for ICP-MS measurement. The detection limit for salinomycin obtained from spiked serum samples was $0.4ag\;mL^{-1}$ (${\pm}10.3%$), which was about $1.5{\times}10^6$ times lower than that of LC-MS/MS and about $1.2{\times}10^{11}$ times better than that of ELISA. Such an excellent sensitivity enabled us to study the toxicity of antibiotics exposed to human beings by determining them in serum.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.100.3-100
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• 2002

This paper presents the method for detection and tracking of multiple humans robustly in mobile platform. The perception of human is performed in real time through the processing of images acquired from a moving stereo vision system. We performed multi-cue integration such as human shape, skin color and depth information to detect and track each human in moving background scene. Human shape is measured by edge-based template matching on distance transformed image. Improving robustness for human detection, we apply the human face skin color in HSV color space. And we could increase the accuracy and the robustness in both detection and tracking by applying random sampling stochastic estimati...

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.87-87
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• 2013

The interface between nanomaterials and biosystems is emerging as one of the broadest and most dynamic areas of science and technology, bringing together biology, chemistry, physics and many areas of engineering, biomedicine. The combination of these diverse areas of research promised to yield revolutionary advances in healthcare, medicine, and life science. For example, the creation of new and powerful nanosensors that enable direct, sensitive, and rapid analysis of biological and chemical species can advance the diagnosis and treatment of disease, discovery and screening of new drug molecules. Nanowire based sensors are emerging as a powerful and general platform for ultrasensitive and multiplex detection of biological and chemical species. Here, we present the studies about noble metal nanowire sensors that can be used for sensitive detection of a wide-range of biological and chemical species including nucleic acids, proteins, and toxic metal ions. Moreover, the optical and electrochemical applications of noble metal nanowires are introduced. Noble metal nanowires are successfully used as plasmonic antennas and nanoelectrodes, thereby provide a pathway for a single molecule sensor, in vivo neural recording, and molecular injection and detection in a single living cell.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1354-1359
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• 2008

In this paper, we propose a vision based passenger monitoring system for passenger's safety in railway station. Since 2005, Korea Railroad Research Institute (KRRI) has developed a vision based monitoring system, funded by Korean government, for passenger's safety in railway station. The proposed system uses various types of sensors, such as, stereo camera, thermal-camera and infrared sensor, in order to detects danger situations in platform area. Especially, detection process of the system exploits the stereo vision algorithm to improve detection accuracy. The paper describes the overall system configuration and proposed detection algorithm, and then verifies the system performance with extensive experimental results in a real station environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1006-1027
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• 2022

In the crowdfunding market, various crowdfunding platforms can offer founders the possibilities to collect funding and launch someone's next campaign, project or events. Especially, healthcare crowdfunding is a field that is growing rapidly on health-related problems based on online platforms. One of the largest platforms, GoFundMe, has raised US$ 5 billion since 2010. Unfortunately, while providing crucial help to care for many people, it is also increasing risk of fraud. Using the largest platform of crowdfunding market, GoFundMe, we conduct an exhaustive search of detection on fraud from October 2016 to September 2019. Data sets are based on 6 main types of medical focused crowdfunding campaigns or events, such as cancer, in vitro fertilization (IVF), leukemia, health insurance, lymphoma and, surgery type. This study evaluated a detect of fraud process to identify fraud from non-fraud healthcare crowdfunding campaigns using various machine learning technics.

• Asia pacific journal of information systems
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• v.28 no.4
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• pp.308-319
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• 2018

This paper aims at providing valuable insights on Financial Fraud Detection on a mobile money transactional activity. We have predicted and classified the transaction as normal or fraud with a small sample and massive data set using Azure and Spark ML, which are traditional systems and Big Data respectively. Experimenting with sample dataset in Azure, we found that the Decision Forest model is the most accurate to proceed in terms of the recall value. For the massive data set using Spark ML, it is found that the Random Forest classifier algorithm of the classification model proves to be the best algorithm. It is presented that the Spark cluster gets much faster to build and evaluate models as adding more servers to the cluster with the same accuracy, which proves that the large scale data set can be predictable using Big Data platform. Finally, we reached a recall score with 0.73, which implies a satisfying prediction quality in predicting fraudulent transactions.