• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1127-1136
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• 2021

In the field of power analysis attacks, electrical noise and misalignment of the power consumption trace are the major factors that determine the success of the attack. Therefore, several studies have been conducted to overcome this problem, and one of them is a signal processing method based on wavelet transform. Up to now, discrete wavelet transform, which can compress the trace, has been mostly used for power side-channel power analysis because continuous wavelet transform techniques increase data size and analysis time, and there is no efficient scale selection method. In this paper, we propose an efficient scale selection method optimized for power analysis attacks. Furthermore, we show that the analysis performance can be greatly improved when using the proposed method. As a result of the CPA(Correlation Power Analysis) and DDLA(Differential Deep Learning Analysis) experiments, which are non-profiling attacks, we confirmed that the proposed method is effective for noise reduction and trace alignment.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.961-968
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• 1999

In this paper we handle a system that transform sensor data to sensor information. Sensor informations from redundant accelerometers are manipulated to represent the configuration of objects carrying sensors. Basic sensor unit of the proposed systme is composed of 3 accelerometers that are aligned along x-y-z coordination axes of motion. To refine the sensor information, at first the sensor data are fused by geometrical optimization to reduce the variance of sensor information. To overcome the error caused from inexact alignment of each sensor to the coordination system, we propose a calibration technique that identifies the transformation between the coordinate axes and real sensor axes. The calibration technique make the sensor information approach real value. Also, we propose a technique that decomposes the accelerometer data into motion acceleration component and gravity acceleration component so that we can get more exact configuration of objects than in the case of raw sensor data. A set of experimental results are given to show the usefulness of the proposed method as well as the experiments in which the proposed techniques are applied to human body motion capture.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.67-73
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• 2005

Recently, the social requirement of personal identification techniques has been increasing. Fingerprint recognition is one of the biometries methods that has been widely used for this requirement. This paper proposes the fingerprint matching algorithm that uses the information of the ridge shapes of minutiae. In which, the data of the ridge shape are expressed in one-dimensional discrete-time signals. In our algorithm, we obtain one-dimensional discrete-time signals for ridge at every minutiae from input and registered fingerprints, and find pairs of minutia which have the similar ridge shape by comparing input fingerprint with registered fingerprint, thereafter we find candidates of rotation angle and moving displacement from the pairs of similar minutia, and obtain the final rotation angle and moving displacement value from those candidates set by using clustering method. After that, we align an input fingerprint by using obtained data, and calculate the matching rate by counting the number of corresponded pairs of minutia within the overlapped area of an input and registered fingerprints. As a result of experiment, false rejection rate(FRR) of $18.0\%$ at false acceptance rate(FAR) of $0.79\%$ is achieved.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.3
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• pp.170-175
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• 2009

In this paper, we propose real time automatic speaker verification (ASV) system to protect personal information on personal digital assistant (PDA) device. Recently, the capacity of PDA has extended and been popular, especially for mobile environment such as mobile commerce (M-commerce). However, there still exist lots of difficulties for practical application of ASV utility to PDA device because it requires too much computational complexity. To solve this problem, we apply the method to relieve the computational burden by performing the preprocessing such as spectral subtraction and speech detection during the speech utterance. Also by applying the hidden Markov model (HMM) optimal state alignment and the sequential probability ratio test (SPRT), we can get much faster processing results. The whole system implementation is simple and compact enough to fit well with PDA device's limited memory and low CPU speed.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.745-752
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• 2024

A method for gamma/neutron event classification based on frequency-domain analysis for mixed radiation environments is proposed. In contrast to the traditional charge comparison method for pulse-shape discrimination, which requires baseline removal and pulse alignment, our method does not need any preprocessing of the digitized data, apart from removing saturated traces in sporadic pile-up scenarios. It also features the identification of neutron events in the detector's full energy range with a single device, from thermal neutrons to fast neutrons, including low-energy pulses, and still provides a superior figure-of-merit for classification. The proposed frequency-domain analysis consists of computing the fast Fourier transform of a triggered trace and integrating it through a simplified version of the transform magnitude components that distinguish the neutron features from those of the gamma photons. Owing to this simplification, the proposed method may be easily ported to a real-time embedded deployment based on Field-Programmable Gate Arrays or Digital Signal Processors. We target an off-the-shelf detector based on a small CLYC (Cs2LiYCl6:Ce) crystal coupled to a silicon photomultiplier with an integrated bias and preamplifier, aiming at lightweight embedded mixed radiation monitors and dosimeter applications.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.181-182
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• 1998

In previous study for correlation between P-wave Signal Averaged Electrocardiography (SAECG) and Paroxysmal Atrial Fibrillation (PAF) subjects, we showed that the duration of P-wave in subjects is longer than in controls. In this respect, the P-wave SAECG is a new method proving to be an accurate and independent noninvasive marker for the risk of PAF. To prove this suggestion, accurate detection and alignment of P-wave are indispensible. In previous study, we measured P-wave duration by manual. So it was not accurate and consistent. To measure the P-wave duration accurately and automatically, we have developed an automatic algorithm for P-wave duration measurement. We showed that the duration of P- wave in the subjects is longer than in controls with this algorithm.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.145-154
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• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• Journal of KIISE
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• v.42 no.10
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• pp.1222-1230
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• 2015

Segmentation of the anterior cruciate ligament (ACL) in knee MRI remains a challenging task due to its inhomogeneous signal intensity and low contrast with surrounding soft tissues. In this paper, we propose a multi-atlas-based segmentation of the ACL in knee MRI with locally-aligned probabilistic atlas (PA) in an iterative graph cuts framework. First, a novel PA generation method is proposed with global and local multi-atlas alignment by means of rigid registration. Second, with the generated PA, segmentation of the ACL is performed by maximum-aposteriori (MAP) estimation and then by graph cuts. Third, refinement of ACL segmentation is performed by improving shape prior through mask-based PA generation and iterative graph cuts. Experiments were performed with a Dice similarity coefficients of 75.0%, an average surface distance of 1.7 pixels, and a root mean squared distance of 2.7 pixels, which increased accuracy by 12.8%, 22.7%, and 22.9%, respectively, from the graph cuts with patient-specific shape constraints.

• Microbiology and Biotechnology Letters
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• v.47 no.4
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• pp.645-650
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• 2019

Despite differences in virulence between strains of Toxoplasma gondii, rapid and accurate genotyping methods are lacking. In this study, a method was developed to detect and genotype T. gondii in food and environmental samples using PCR and a novel peptide nucleic acid (PNA) melting array. An alignment of genome sequences for T. gondii type I, II, and III obtained from NCBI was generated, and a single nucleotide polymorphism analysis was performed to identify targets for PCR amplification and a PNA melting array. Prior to the PNA melting array, conventional PCR was used to amplify GRA6 of T. gondii. After amplification, the PNA melting array was performed using two different PNA hybridization probes with fluorescent labels (FAM and HEX) and quenchers. Melting curves for each probe were used to determine genotypes and identify mutations. A 214-bp region of the GRA6 gene of T. gondii was successfully amplified by PCR. For all T. gondii strains (type I, II, and III) used to evaluate specificity, the correct genotypes were determined by the PNA melting array. Non-T. gondii strains, including 14 foodborne pathogens and 3 protozoan parasites, such as Giardia lamblia, Cryptosporidium parvum, and Entamoeba histolytica, showed no signal, suggesting that the assay has a high specificity. Although this is only a proof-of-concept study, the assay is promising for the fast and reliable genotyping of T. gondii from food and environmental samples.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.57-63
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• 2018

In the case of aircraft-launched guided weapons, various interface tests such as MIL-STD-1760 based power source, discrete signal, MUX communication as well as BIT of missile can verify system safety and reliability. The purpose of this case study is to develop a test bench based on MIL-STD-1760E for interoperability testing between aircraft and weapons. We proposed a testing method of the launch sequence based on the defined TIME LINE in the development phase of the missile system from the application of the power of the missile to the targeting, the transfer order, and the missile separation process. Furthermore, it will be a reference model that can maximize the verification scope in the development phase of the air to surface missile system by simulating abnormal situation to the inert missile using the error insertion function.