• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.161-166
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• 2014

This Electromagnetic metal piece detection sensor, having high sensitivity even under high humidity and dust density, using LVDT was investigated. Metal detection characteristics using phase detection method, for 3 frequencies covering ELF and LF band, were experimentally measured. It was found that the sensitivity for metal and animal food, in which metal piece was included, was exponentially increased as frequency increased. Reducing cutoff frequency of LPF after PD was found to be effective to proportionally increase sensitivity. Also the sensitivity of metal piece detection was enhanced by optimizing BPF bandwidth and SNR. Metal piece detection limit using available ferrous test samples was found to be 0.7mm diameter from the experiment using 50kHz, in ELF band, which was known to have better selectivity to animal food. is an example of ABSTRACT format.

• Journal of Korean Neurosurgical Society
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• v.65 no.2
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• pp.315-324
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• 2022

Objective : The aim of this study was to verify the equivalence and effectiveness of the tablet-administered Korean Repeatable Battery for the Assessment of Neuropsychological Status (K-RBANS) for the prevention and early detection of dementia. Methods : Data from 88 psychiatry and neurology patient samples were examined to evaluate the equivalence between tablet and paper administrations of the K-RBANS using a non-randomly equivalent group design. We calculated the prediction scores of the tablet-administered K-RBANS based on demographics and covariate-test scores for focal tests using norm samples and tested format effects. In addition, we compared the receiver operating characteristic curves to confirm the effectiveness of the K-RBANS for preventing and detecting dementia. Results : In the analysis of raw scores, line orientation showed a significant difference (t=-2.94, p<0.001), and subtests showed small to large effect sizes (0.04-0.86) between paper- and tablet-administered K-RBANS. To investigate the format effect, we compared the predicted scaled scores of the tablet sample to the scaled scores of the norm sample. Consequently, a small effect size (d≤0.20) was observed in most of the subtests, except word list and story recall, which showed a medium effect size (d=0.21), while picture naming and subtests of delayed memory showed significant differences in the one-sample t-test. In addition, the area under the curve of the total scale index (TSI) (0.827; 95% confidence interval, 0.738-0.916) was higher than that of the five indices, ranging from 0.688 to 0.820. The sensitivity and specificity of TSI were 80% and 76%, respectively. Conclusion : The overall results of this study suggest that the tablet-administered K-RBANS showed significant equivalence to the norm sample, although some subtests showed format effects, and it may be used as a valid tool for the brief screening of patients with neuropsychological disorders in Korea.

• Parasites, Hosts and Diseases
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• v.54 no.1
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• pp.1-8
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• 2016

Laboratory workers, in resource-poor countries, still consider PCR detection of Giardia lamblia more costly and more time-consuming than the classical parasitological techniques. Based on 2 published primers, an in-house one-round touchdown PCR-RFLP assay was developed. The assay was validated with an internal amplification control included in reactions. Performance of the assay was assessed with DNA samples of various purities, 91 control fecal samples with various parasite load, and 472 samples of unknown results. Two cysts per reaction were enough for PCR detection by the assay with exhibited specificity (Sp) and sensitivity (Se) of 100% and 93%, respectively. Taking a published small subunit rRNA reference PCR test results (6%; 29/472) as a nominated gold standard, G. lamblia was identified in 5.9% (28/472), 5.2%, (25/472), and 3.6% (17/472) by PCR assay, $RIDA^{(R)}$ Quick Giardia antigen detection test (R-Biopharm, Darmstadt, Germany), and iodine-stained smear microscopy, respectively. The percent agreements (kappa values) of 99.7% (0.745), 98.9% (0.900), and 97.7% (0.981) were exhibited between the assay results and that of the reference PCR, immunoassay, and microscopy, respectively. Restriction digestion of the 28 Giardia-positive samples revealed genotype A pattern in 12 and genotype B profile in 16 samples. The PCR assay with the described format and exhibited performance has a great potential to be adopted in basic clinical laboratories as a detection tool for G. lamblia especially in asymptomatic infections. This potential is increased more in particular situations where identification of the parasite genotype represents a major requirement as in epidemiological studies and infection outbreaks.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.179-185
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• 2012

This paper proposes a design of RSIDS(RST and SVM based Intrusion Detection System) using RST(Rough Set Theory) and SVM(Support Vector Machine) algorithm. The RSIDS consists of PrePro(PreProcessing) module, RRG(RST based Rule Generation) module, and SAD(SVM based Attack Detection) module. The PrePro module changes the collected information to the data format of RSIDS. The RRG module analyzes attack data, generates the rules of attacks, extracts attack information from the massive data by using these rules, and transfers the extracted attack information to the SAD module. The SAD module detects the attacks by using it, which the SAD module notifies to a manager. Therefore, compared to the existing SVM, the RSIDS improved average ADR(Attack Detection Ratio) from 77.71% to 85.28%, and reduced average FPR(False Positive ratio) from 13.25% to 9.87%. Thus, the RSIDS is estimated to have been improved, compared to the existing SVM.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.451-457
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• 2020

Format recognition and OCR techniques are widely used as methods for detecting and protecting personal information from electronic documents. However, due to the poor recognition rate of the OCR engine, personal information cannot be detected or false positives commonly occur. It also takes a long time to analyze a large amount of electronic documents. In this paper, we propose a method to improve the speed of image analysis of electronic documents, character recognition rate of the OCR engine, and detection rate of personal information by improving the existing method. The analysis speed was increased using the format recognition method while the analysis speed and character recognition rate of the OCR engine was improved by image correction. An algorithm for analyzing personal information from images was proposed to increase the reconnaissance rate of personal information. Through the experiments, 1755 image format recognition samples were analyzed in an average time of 0.24 seconds, which was 0.5 seconds higher than the conventional PAID system format recognition method, and the image recognition rate was 99%. The proposed method in this paper can be used in various fields such as public, telecommunications, finance, tourism, and security as a system to protect personal information in electronic documents.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.167-177
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• 2013

In this paper, a motion adaptive deinterlacing algorithm is proposed. It consists of three parts: (1) modified edge-based line average, (2) pixel-based consequent five-field motion detection, and (3) block-based local characteristic for detecting true motion and calculating the motion intensity by using an improved method which is able to detect the inner part of moving objects precisely as well as to reduce the risk of false detection caused by intrinsic noises in the image. Depending on the detected motion activity level, it combines spatial and temporal methods with weighting factor. Simulations conducted on several video sequences indicate that the performance of the proposed method is superior to the conventional methods in terms of both subjective and objective video quality.

• Journal of Microbiology and Biotechnology
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• v.13 no.4
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• pp.509-516
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• 2003

A model system for the immnunochemical detection of Escherichia coli O157:H7 using a combined immunomagnetic separation (IMS) and test-strip liposome immunoassay (LIA) procedure was developed. Immunomagnetic beads coated with anti-E. coli O157 IgG antibodies were used to separate the E. coli O157 (including the H7 serotype) from culture. Immunoliposomes, whose surface was conjugated to goat anti-E. coli O157:H7 IgG and which encapsulated the marker dye, sulforhodamine B, were used as a detection label. The test strip, onto which antibodies to goat IgG were immobilized, was the immunosensor capturing immunoliposomes that did not bind to E. coli O157:H7 on the immunomagnetic bead-E. coli O157:H7 complexes. In experiments, pure cell culture suspensions of $10^5 E.$ coli O157:H7 organisms per ml produced a measurable signal inhibition, whereas a weak yet detectable signal inhibition occurred with $10^3CFU/ml$. The inhibition signals increased, when the incubation time for IMS was extended to 90 min and higher IgG-tag density (0.4mol%) was used on the liposomes. With 0.2 and 0.4mol% IgG-tagged liposomes, the IMS-LIA procedure showed more improved signal inhibitions than those of a direct (no IMS) LIA. The combined assay, which measures the instantaneous signal from immunoliposomes, can be completed within 90 min, making it significantly faster than conventional plating methods and enzyme-linked immunosorbent assay (ELISA). Accordingly, it is quite feasible to use the combined immunoassay format of IMS and dye-loaded immunoliposomes for the detection of E. coli O157:H7.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.175-182
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• 2022

In our daily life, we come across different types of information, for example in the format of multimedia and text. We all need different types of information for our common routines as watching/reading the news, listening to the radio, and watching different types of videos. However, sometimes we could run into problems when a certain type of information is required. For example, someone is listening to the radio and wants to listen to jazz, and unfortunately, all the radio channels play pop music mixed with advertisements. The listener gets stuck with pop music and gives up searching for jazz. So, the above example can be solved with an automatic audio classification system. Deep Learning (DL) models could make human life easy by using audio classifications, but it is expensive and difficult to deploy such models at edge devices like nano BLE sense raspberry pi, because these models require huge computational power like graphics processing unit (G.P.U), to solve the problem, we proposed DL model. In our proposed work, we had gone for a low complexity model for Audio Event Detection (AED), we extracted Mel-spectrograms of dimension 128×431×1 from audio signals and applied normalization. A total of 3 data augmentation methods were applied as follows: frequency masking, time masking, and mixup. In addition, we designed Convolutional Neural Network (CNN) with spatial dropout, batch normalization, and separable 2D inspired by VGGnet [1]. In addition, we reduced the model size by using model quantization of float16 to the trained model. Experiments were conducted on the updated dataset provided by the Detection and Classification of Acoustic Events and Scenes (DCASE) 2020 challenge. We confirm that our model achieved a val_loss of 0.33 and an accuracy of 90.34% within the 132.50KB model size.

• International Journal of Contents
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• v.10 no.4
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• pp.63-68
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• 2014

In this paper, we propose a smart system that can optically recognize a music score within a document and can play the music after recognition. Many historic handwritten documents have now been digitalized. Converting images of a music score within documents into digital files is particularly difficult and requires considerable resources because a music score consists of a 2D structure with both staff lines and symbols. The proposed system takes an input image using a mobile device equipped with a camera module, and the image is optimized via preprocessing. Binarization, music sheet correction, staff line recognition, vertical line detection, note recognition, and symbol recognition processing are then applied, and a music file is generated in an XML format. The Music XML file is recorded as digital information, and based on that file, we can modify the result, logically correct errors, and finally generate a MIDI file. Our system reduces misrecognition, and a wider range of music score can be recognized because we have implemented distortion correction and vertical line detection. We show that the proposed method is practical, and that is has potential for wide application through an experiment with a variety of music scores.

• Journal of IKEEE
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• v.3 no.1 s.4
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• pp.22-28
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• 1999

The existing CREG-VP, a technique to compensate the successive cell losses caused by traffic congestion using the FEC method on the Vp, has the merits of the short average encoding decoding time and the compatibility with the ATM standard cell format, but it has the restriction in the number of regenerable cells. In this thesis, we propose a scheme to efficiently regenerate the cell losses even in the burst traffic property by the expansion of the CREG-VP. The proposed scheme improves the detection capability of the lost cells by changing the CRP and the regeneration performance of the successive cells by using the interleaved parity cell. The simulation result shows that the proposed method produces much improvements compared with the existing ones in the cell loss rate reduction factor.