• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.416-422
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• 2021

Due to the large differences in human activity within classes, the large similarity between classes, and the problems of visual angle and occlusion, it is difficult to extract features manually, and the detection rate of human behavior is low. In order to better solve these problems, an improved Faster R-CNN-based detection algorithm is proposed in this paper. It achieves multi-object recognition and localization through a second-order detection network, and replaces the original feature extraction module with Dense-Net, which can fuse multi-level feature information, increase network depth and avoid disappearance of network gradients. Meanwhile, the proposal merging strategy is improved with Soft-NMS, where an attenuation function is designed to replace the conventional NMS algorithm, thereby avoiding missed detection of adjacent or overlapping objects, and enhancing the network detection accuracy under multiple objects. During the experiment, the improved Faster R-CNN method in this article has 84.7% target detection result, which is improved compared to other methods, which proves that the target recognition method has significant advantages and potential.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.130-138
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• 2024

High-precision 3D Object Detection is a crucial component within autonomous driving systems, with far-reaching implications for subsequent tasks like multi-object tracking and path planning. In this paper, we propose a novel approach designed to enhance the performance of 3D Object Detection, especially in heading angle estimation by employing a moving object segmentation technique. Our method starts with extracting point-wise moving labels via a process of moving object segmentation. Subsequently, these labels are integrated into the LiDAR Pointcloud data and integrated data is used as inputs for 3D Object Detection. We conducted an extensive evaluation of our approach using the KITTI-road dataset and achieved notably superior performance, particularly in terms of AOS, a pivotal metric for assessing the precision of 3D Object Detection. Our findings not only underscore the positive impact of our proposed method on the advancement of detection performance in lidar-based 3D Object Detection methods, but also suggest substantial potential in augmenting the overall perception task capabilities of autonomous driving systems.

• Advances in nano research
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• v.9 no.1
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• pp.1-13
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• 2020

In this work, the electrical potential (EP) technique with an artificial neural networks (ANNs) for monitoring of nanostructures are used for the first time. This study employs an expert system to identify size and localize hidden nano-delamination (N.Del) inside layers of nano-pipe (N.P) manufactured from Basalt Fiber Reinforced Polymer (BFRP) laminate composite by using low-cost monitoring method of electrical potential (EP) technique with an artificial neural networks (ANNs), which are combined to decrease detection effort to discern N.Del location/size inside the N.P layers, with high accuracy, simple and low-cost. The dielectric properties of the N.P material are measured before and after N.Del introduced using arrays of electrical contacts and the variation in capacitance values, capacitance change and node potential distribution are analyzed. Using these changes in electrical potential due to N.Del, a finite element (FE) simulation model for N.Del location/size detection is generated by ANSYS and MATLAB, which are combined to simulate sensor characteristic, therefore, FE analyses are employed to make sets of data for the learning of the ANNs. The method is applied for the N.Del monitoring, to minimize the number of FE analysis in order to keep the cost and save the time of the assessment to a minimum. The FE results are in excellent agreement with an ANN and the experimental results available in the literature, thus validating the accuracy and reliability of the proposed technique.

• Bulletin of the Korean Chemical Society
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• v.34 no.12
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• pp.3835-3839
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• 2013

A new synthesis route for Pt nanoparticles by direct electrochemical reduction of a solid-state Pt ion precursor ($K_2PtCl_6$) is demonstrated. Solid $K_2PtCl_6$-supported polyethyleneimine (PEI) coatings on the surface of glassy carbon electrode were prepared by simple mixing of solid $K_2PtCl_6$ into a 1.0% PEI solution. The potential cycling or a constant potential in a PBS (pH 7.4) medium were applied to reduce the solid $K_2PtCl_6$ precursor. The reduction of Pt(IV) began at around -0.2 V and the reduction potential was ca. -0.4 V. A steady state current was achieved after 10 potential cycling scans, indicating that continuous formation of Pt nanoparticles by electrochemical reduction occurred for up to 10 cycles. After applying the reduction potential of -0.6 V for 300 s, Pt nanoparticles with diameters ranging from $0.02-0.5{\mu}m$ were observed, with an even distribution over the entire glassy carbon electrode surface. Characteristics of the Pt nanoparticles, including their performance in electrochemical reduction of $H_2O_2$ are examined. A distinct reduction peak observed at about -0.20 V was due to the electrocatalytic reduction of $H_2O_2$ by Pt nanoparticles. From the calibration plot, the linear range for $H_2O_2$ detection was 0.1-2.0 mM and the detection limit for $H_2O_2$ was found to be 0.05 mM.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7583-7588
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• 2014

Background: Colorectal cancer (CRC) is a major cause of cancer-related death and cancer-related incidence worldwide. The potential of microRNA-21 (miR-21) as a biomarker for CRC detection has been studied in several studies. However, the results were inconsistent. Therefore, we conducted the present meta-analysis to systematically assess the diagnostic value of miR-21 for CRC. Materials and Methods: Using a random-effect model, the pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were calculated to evaluate the diagnostic performance of miR-21 for CRC. A summary receiver operating characteristic (SROC) curve and an area under the curve (AUC) were also generated to assess the diagnosis accuracy of miR-21 for CRC. Q test and I2 statistics were used to assess between-study heterogeneity. Publication bias was evaluated by the Deeks' funnel plot asymmetry test. Results: A total of 986 CRC patients and 702 matched healthy controls from 8 studies were involved in the meta-analysis. The pooled results for SEN, SPE, PLR, NLR, DOR, and AUC were 57% (95%CI: 39%-74%), 87% (95%CI: 78%-93%), 4.4 (95%CI: 2.4-8.0), 0.49 (95%CI: 0.32-0.74), 9 (95%CI: 4-22), and 0.83 (95%CI: 0.79-0.86), respectively. Subgroup analyses further suggested that blood-based studies showed a better diagnostic accuracy compared with feces-based studies, indicating that blood may be a better matrix for miR-21 assay and CRC detection. Conclusions: Our findings suggest that miR-21 has a potential diagnostic value for CRC with a moderate level of overall diagnostic accuracy. Hence, it could be used as auxiliary means for the initial screening of CRC and avoid unnecessary colonoscopy, which is an invasive and expensive procedure.

• Journal of Medicine and Life Science
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• v.17 no.1
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• pp.29-32
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• 2020

As respiratory syncytial virus(RSV) is transmitted either via directly contact with an infected case or via indirectly contaminated fomites or skin, the major preventive measures are strict hand hygiene, early detection of transmitted sources, and rapid isolation of RSV patients. Especially early detection of hidden cases is the most critical control measure when an index case was notified in a postpartum center. The Guideline of Korea Centers for Diseases Control and Prevention defines potential contacts in an epidemiologic survey as admitted newborns, parents of index cases, center's workers, and visitors for 10 days before the first diagnosis day of index case. However, it needs to classify potential contacts in more detail in order to conduct a successful survey. Authors conducted to search related literatures and appraise the evidences. Firstly, potential contacts would be classified into RSV-related symptomatic contacts(SxC) and asymptomatic contacts. And then, mother, caring workers, and visitors of the index cases among asymptomatic contacts would be defined as the asymptomatic close contacts(ASCC). Finally, the rest would be defined as the asymptomatic regular contacts(ASRC). The defined test using reverse transcription-PCR is applied to SxC and ASCC, and decision of isolation or regular activities are made according to the results. The rapid antigen detection test kits are applied to ASRC. These suggestions might be helpful to detect hidden cases earlier and prevent a further infection.

• Bulletin of the Korean Chemical Society
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• v.32 no.11
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• pp.3959-3962
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• 2011

A simple propargylamide-fuctionalized chemodosimeter was prepared for the ratiometric fluorescence detection of mercuric ions in HEPES buffer. The chemodosimeter exhibited $Hg^{2+}$-induced propargyl amide-tooxazole transformation, with a significant accompanying ratiometric change in fluorescence. It afforded high selectivity for mercuric ion detection without any competitive inhibition by common alkali, alkaline earth, or other transition metal ions. The probe showed a $17{\times}10^{-6}M$ detection limit for $Hg^{2+}$ ions and potential applicability for detecting aqueous $Hg^{2+}$ ions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.268-271
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• 1998

this paper presents the potential application of fuzzy logic to the automatic incident detection system. While the conventional incident detection algorithms are based on a binary decision process, the algorithm using fuzzy logic can incorporate ambiguity which occurs in determining incidents. Since collecting good amount of data to construct data base for incidents is pretty expensive, a traffic simulator called FRESIM is used to simulate traffic condition in a freeway. Incident data are obtained by changing input parameters of the simulator and the fuzzy algorithm generates fuzzy rule for determining normal and incident traffic conditions. In this paper, various steps are described to test the algorithm and its results are summarized.

• Journal of Sensor Science and Technology
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• v.23 no.4
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• pp.217-223
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• 2014

Nerve agents are major chemical warfare agents with the "G series" and "V series" being the most widely known because of their lethal effect. Although not conspicuously used in major wars, the potential detrimental impact on modern society had been revealed from the sarin terror attack on Tokyo subway, which affected thousands of people. In this mini-review, major nerve agents of the "G series" and "V series" have been described along with various types of their detection methods. The physical properties and hydrolysis mechanisms of the major nerve agents are discussed since these are important factors to be considered in choosing detection methods, and specifying the procedures for sample preparations in order to enhance detection precision. Various types of extraction methods, including liquid-phase, solid-phase, gas-phase and solid-phase microextraction (SPME), are described. Recent development in the use of gas sensors for detecting nerve agents is also summarized.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.1
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• pp.17-24
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• 2012

We address some potential problems with the existing procedures of outlier detection in time series. Also we propose modifications in estimating model parameters and outlier effects in order to reduce the number of tests and to increase the detection accuracy. Experiments with some artificial data sets show that the proposed procedure significantly reduces the number of tests and enhances the accuracy of estimated parameters as well as the detection power.