• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.135-140
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• 2014

As the digital image devices are widely used, interests in the software- and the hardware-related image processing become higher and the image processing techniques are applied in various fields such as object recognition, object detection, fingerprint recognition, and etc. For the edge detections Sobel, Prewitt, Laplacian, Roberts and Canny detectors are used and these existing methods can excellently detect the edges of the images without noise. However, in the images corrupted by the impulse noise, these methods are insufficent in noise elimination characteristics, showing unsatisfactory edge detection. Therefore in this paper, in order to obtain excellent edge detection characteristics in the corrupted image by the impulse noise, an detection algorithm is porposed, which uses the central pixel of mask divided by four regions along the axis, calculates the estimated mask according to the representing pixel values in each regions, and detects the final edges by applying the estimates mask and the new directional one.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.6
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• pp.95-105
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• 2003

A novel reference point detection method is proposed by exploiting tile gradient probabilistic model that captures the curvature information of fingerprint. The detection of reference point is accomplished through searching and locating the points of occurrence of the most evenly distributed gradient in a probabilistic sense. The uniformly distributed gradient texture represents either the core point itself or those of similar points that can be used to establish the rigid reference from which to map the features for recognition. Key benefits are reductions in preprocessing and consistency of locating the same points as the reference points even when processing arch type fingerprints. Moreover, the new feature extraction method is proposed by improving the existing feature extraction using filterbank method. Experimental results indicate the superiority of tile proposed scheme in terms of computational time in feature extraction and verification rate in various noisy environments. In particular, the proposed gradient probabilistic model achieved 49% improvement under ambient noise, 39.2% under brightness noise and 15.7% under a salt and pepper noise environment, respectively, in FAR for the arch type fingerprints. Moreover, a reduction of 0.07sec in reference point detection time of the GPM is shown possible compared to using the leading the poincare index method and a reduction of 0.06sec in code extraction time of the new filterbank mettled is shown possible compared to using the leading the existing filterbank method.

• Corrosion Science and Technology
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• v.16 no.4
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• pp.194-200
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• 2017

Stress-corrosion cracking (SCC) of alloy 600 and alloy 800 in 0.5 mol/L thiosulfate solution during constant strain was investigated using electrochemical noise (EN) combined with 3-D microscope techniques. The in-situ morphology observation and EN results indicate that the SCC process could be divided into three stages: (1) passive film stabilization and growth, (2) crack initiation, (3) and crack growth. Power Spectral Density (PSD) and the probability distribution obtained from EN were used as the "fingerprint" to distinguish the different processes. During passive film stabilization and growth, the current noise signals resembled "white noise": when the crack initiated, many transient peaks could be seen in the current noise and the wavelet energy at low frequency as well as the noise resistance decreased. After crack propagation, the noise amplitudes increased, particularly the white noises at low and high frequencies ($W_L$ and $W_H$) in the PSDs. Finally, the detection of metal structure corrosion in a simulated sea splash zone and pipeline corrosion in the atmosphere are established.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1939-1943
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• 2012

In this paper we presented the detection of the explosive material RDX using a parallel plate waveguide (PPWG) THz time domain spectroscopy (TDS). Normally the explosive materials have been characterized through identification of vibrational fingerprint spectra. Until now, most of all THz spectroscopic measurements have been made using pellet samples where disorder effects contribute to line broadening such that individual resonances merge into relatively broad absorption features. In order to avoid such disadvantages we used the technique of PPWG THz-TDS to achieve sensitive characterization of explosive material RDX. The PPWG THz-TDS used in this work well established ultrafast optoelectronic techniques to generate and detect sub-picosecond THz pulses. The explosive material was analyzed as powder layers in $112{\mu}m$ gap of metal PPWG. The thin later mass was estimated to be about $700{\mu}g$. Finally, we showed spectra of explosives from 0.2 to 2.4 THz measured using PPWG THz-TDS.

• Smart Structures and Systems
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• v.5 no.2
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• pp.153-171
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• 2009

In this paper, the analytical fault detection and diagnosis (FDD) is presented using model-based and signal-based methodology with wavelet analysis on signals obtained from sensors and sensor networks. In the model-based FDD, we present the modeling of contact interface found in soft materials, including the biomedical contacts. Fingerprint analysis and signal-based FDD are also presented with an experimental framework consisting of a mechanical pneumatic system typically found in manufacturing automation. This diagnosis system focuses on the signal-based approach which employs multi-resolution wavelet decomposition of various sensor signals such as pressure, flow rate, etc., to determine leak configuration. Pattern recognition technique and analytical vectorized maps are developed to diagnose an unknown leakage based on the established FDD information using the affine mapping. Experimental studies and analysis are presented to illustrate the FDD methodology. Both model-based and wavelet-based FDD applied in contact interface and manufacturing automation have implication towards better quality of life by applying theory and practice to understand how effective diagnosis can be made using intelligent FDD. As an illustration, a model-based contact surface technology an benefit the diabetes with the detection of abnormal contact patterns that may result in ulceration if not detected and treated in time, thus, improving the quality of life of the patients. Ultimately, effective diagnosis using FDD with wavelet analysis, whether it is employed in biomedical applications or manufacturing automation, can have impacts on improving our quality of life.

• CELLMED
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• v.10 no.1
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• pp.7.1-7.6
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• 2020

Plants produce a wide range of active principles, making them a rich source of different types of medicines. Without any knowledge of the phytoconstituents or active principles the medicinal plants itself or in the form of polyherbal formulations, were used by all society of human being from ancient times for prevention and cure of disease, but most of the traditional formulations including the formulation of Ayurveda and Unani have not been scientifically validated in order to establish the pharmacopoeial standards to improve the efficacy. Globally, the people become conscious that uses of synthetic drugs for a long period is not safe; the trend of medical society at large is looking at alternatives from natural, safe sources to combat diseases. Due to this comprehension, it has been increased the demand for plant-derived medicine, and on the other side, it is extremely important to standardize the polyherbal formulations and validate them scientifically to improve their safety and efficacy. The polyherbal Unani formulation Safuf-e-Muallif is widely used and recommended in Unani system of medicine (USM) as a spermatogenic agent, semen thickening agent, etc. to treat sexual disorders viz. premature ejaculation, nocturnal emission, etc. The study mainly deals with phytochemical screening for the detection of nature of phytoconstituents and analytical technique like High-performance thin-layer chromatography (HPTLC) for developing fingerprint of Safuf-e-Muallif revealing specific identities of the drug. The phytochemical screening and HPTLC fingerprint profile for SM reported here may be used as a reference standard for quality control purpose in future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1934-1942
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• 2015

An estimation problem in the environment which GPS signals do not reach, should be solved by employing an indoor location estimation scheme. Location estimation schemes for indoor environments generally include the AOA, TOA, RSS, Fingerprint, and TDOA. For a ship environment where there exist many spaces enclosed by iron plates, the TDOA scheme is appropriate because location estimation is usually performed at a closed range. In this paper, we address the problem of estimating the location of a terminal under the ship environment. The problem of location estimation by using the TDOA is presented in detail, and then an algorithm for applying the estimation to the ship environment is proposed. Finally, the proposed algorithm of location estimation in a ship by the TDOA scheme is verified through simulations from three viewpoints.

• The Journal of Korean Medicine
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• v.25 no.3
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• pp.45-54
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• 2004

Objectives : This study was aimed to evaluate marker substances in Gami-Honghwa-Tang (KH-19) by high performance liquid chromatography-photodiode array detector (HPLC-DAD). Gami-Honghwa-Tang is composed of nine crude herbs, Rehmanniae Radix Preparata, Angelicae Gigantis Radix, Cnidii Rhizoma, Paeoniae Radix, Corni Fructus, Moutan Cortex Radicis, Lycii Fructus, Carthami Flos and Glycyrrhizae Radix. Methods : The separation was performed on an Aquasil C18 (4.6×250mm) column by gradient elution with 0.05% TFA in H2O - 0.05% TFA in acetonitrile (0 min 100:0, 20 min 90:10, 40 min 70:30, 60 min 50:50, 80 min 0:100, 90 min 100:0) as the mobile phase at a flow-rate of 1.0 ml/min with detection at 190-800nm. Also we examined the contents for bacteria, pesticide residue and harmful heavy metals. Results : HPLC-DAD was employed to determine the quantities and the qualities of several marker substances such as 5­hydroxymethyl-2-furaldehyde (5-HMF), paeonol, loganin, paeoniflorin, glycyrrhizin, and decursin in the KH-19. There were no bacterial contents, pesticide residues, or harmful heavy metals. Conclusions : We suggest these results could be a useful evidence for quality control of KH-19. This method permits fingerprints of selected individual marker substances from herbal prescriptions without derivatization, multiple purification steps, or lengthy separation times.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.369-379
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• 2022

In weighted k-nearest neighbor (WkNN)-based Fingerprinting positioning step, a process of comparing the requested positioning signal with signal information for each reference point stored in the fingerprint DB is performed. At this time, the higher the number of matched base station identifiers, the higher the possibility that the terminal exists in the corresponding location, and in fact, an additional weight is added to the location in proportion to the number of matching base stations. On the other hand, if the matching number of base stations is small, the selected candidate reference point has high dependence on the similarity value of the signal. But one problem arises here. The positioning signal can be compared with the repeater signal in the signal information stored on the DB, and the corresponding reference point can be selected as a candidate location. The selected reference point is likely to be an outlier, and if a certain weight is applied to the corresponding location, the error of the estimated location information increases. In order to solve this problem, this paper proposes a WkNN technique including an outlier removal function. To this end, it is first determined whether the repeater signal is included in the DB information of the matched base station. If the reference point for the repeater signal is selected as the candidate position, the reference position corresponding to the outlier is removed based on the clustering technique. The performance of the proposed technique is verified through data acquired in Seocho 1 and 2 dongs in Seoul.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.132-146
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• 2020

Biometric technologies have become widely available in many different fields. However, biometric technologies using existing physical features such as fingerprints, facial features, irises, and veins must consider forgery and alterations targeting them through fraudulent physical characteristics such as fake fingerprints. Thus, a trend toward next-generation biometric technologies using behavioral biometrics of a living person, such as bio-signals and walking characteristics, has emerged. Accordingly, in this study, we developed a bio-signal authentication algorithm using electrocardiogram (ECG) signals, which are the most uniquely identifiable form of bio-signal available. When using ECG signals with our system, the personal identification and authentication accuracy are approximately 90% during a state of rest. When using fingerprints alone, the equal error rate (EER) is 0.243%; however, when fusing the scores of both the ECG signal and fingerprints, the EER decreases to 0.113% on average. In addition, as a function of detecting a presentation attack on a mobile phone, a method for rejecting a transaction when a fake fingerprint is applied was successfully implemented.