• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4808-4824
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• 2016

Signal individual reconnaissance and identification is an extremely important research topic in non-cooperative domains such as electronic countermeasures and intelligence reconnaissance. Facing the characteristics of the complexity and changeability of current communication environment, how to realize radiation source signal individual identification under the low SNR conditions is an emphasis of research. A novel emitter individual identification method combined bi-spectrum analysis with wavelet feature is presented in this paper. It makes a feature fusion of bi-spectrum slice characteristics and energy variance characteristics of the secondary wavelet transform coefficient to identify MFSK signals under the low SNR (signal-to-noise ratios) environment. Theoretical analyses and computer simulation results show that the proposed algorithm has good recognition performance with the ability to suppress noise and interference, and reaches the recognition rate of more than 90% when the SNR is -6dB.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.18-22
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• 2006

This paper proposes the framework of the scenario-based 3D image synthesizing system that allows common users who envision a scenario in their mind to realize it into the segments of cool animation. We focused on utilization of the existing motions to synthesize new motions for the objects. The framework is useful to build a 3D animation in game programming with a limited set of 3D objects. We also propose a practical algorithm to reuse and expand the objects. This algorithm is based on motion path modification rules. Both linear and nonlinear curve-fitting algorithms were applied to modify an animation by key frame interpolation and to make the motion appear realistic.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.431-438
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• 2017

In this paper, the abdomen ECG(AECG) is employed to measure the mother's ECG instead of the conventioanl thoracic ECG measurement. The fetus ECG signal can be extracted from the AECG using an algorithm that utilizes the mobile fetal ECG measurement platform, which is based on the BLE (Bluetooth Low Energy). The algorithm has been implemented by using a replacement processor processed directly from the platform BLE instead of the large statistical data processing required in the ICA(Independent component analysis). The proposed algorithm can be implemented on a mobile BLE wireless ECG system hardware platform to process the maternal ECG. Wireless technology can realize a compact, low-power radio system for short distance communication and the IOT(Intenet of Things) enables the transmission of real-time ECG data. It was also implemented in the form of a compact module in order for mothers to be able to download and store the collected ECG data without having to interrupt or move the logger, and later link the module to a computer for downloading and analyzing the data. A mobile ECG measurement prototype is manufactured and tested to measure the FECG for pregnant women. The experimental results verify a real-time FECG extraction capability for the proposed system. In this paper, we propose an ECG measurement system that shows approximately 91.65% similarity to the MIT database and the conventional algorithm and SNR performance about 10% better.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.11-17
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• 2014

As ICT Ecosystem does, electronic government changes in its form. Accordingly, in order to realize Smarter m-Gov, the governments need to vitalize m-Gov services and enact technology policy. Therefor, this manuscript suggests possible model of m-Gov realization and security algorithm as a technology policy which applies quantum cryptography system to server security for the construction of secured m-Gov's infrastructure. What the manuscript suggests seeks administrative ideas of Smarter m-Gov's services which contain security, stability, and economic feasibility for the benefits of nation and enterprises.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.265-267
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• 2013

Edges include various important informations of the objects. These edges are being applied in numerous areas and there is a detection method using mask in existing edge detection methods. These existing edge detection methods are simple to realize. However, because the fixed mask is used, edge detection characteristics in complicated noise environments are somewhat unsatisfactory. Therefore, to compensate for the weakness in the existing detection methods, edge detection algorithm which uses the standard deviation of local mask and noise elimination was proposed.

• Smart Structures and Systems
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• v.23 no.2
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• pp.107-122
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• 2019

As one of the most important parameters in structural health monitoring, structural frequency has many advantages, such as convenient to be measured, high precision, and insensitive to noise. In addition, frequency-change-ratio based method had been validated to have the ability to identify the damage occurrence and location. However, building a precise enough finite elemental model (FEM) for the test structure is still a huge challenge for this frequency-change-ratio based damage detection technique. In order to overcome this disadvantage and extend the application for frequencies in structural health monitoring area, a novel method was developed in this paper by combining the cross-model cross-mode (CMCM) model updating algorithm with the frequency-change-ratio based method. At first, assuming the physical parameters, including the element mass and stiffness, of the test structure had been known with a certain value, then an initial to-be-updated model with these assumed parameters was constructed according to the typical mass and stiffness distribution characteristic of shear buildings. After that, this to-be-updated model was updated using CMCM algorithm by combining with the measured frequencies of the actual structure when no damage was introduced. Thus, this updated model was regarded as a representation of the FEM model of actual structure, because their modal information were almost the same. Finally, based on this updated model, the frequency-change-ratio based method can be further proceed to realize the damage detection and localization. In order to verify the effectiveness of the developed method, a four-level shear building was numerically simulated and two actual shear structures, including a three-level shear model and an eight-story frame, were experimentally test in laboratory, and all the test results demonstrate that the developed method can identify the structural damage occurrence and location effectively, even only very limited modal frequencies of the test structure were provided.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2107-2119
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• 2022

Accurate remaining useful life (RUL) prediction for critical components of nuclear power equipment is an important way to realize aging management of nuclear power equipment. The electric gate valve is one of the most safety-critical and widely distributed mechanical equipment in nuclear power installations. However, the electric gate valve's extended service in nuclear installations causes aging and degradation induced by crack propagation and leakages. Hence, it is necessary to develop a robust RUL prediction method to evaluate its operating state. Although the particle filter(PF) algorithm and its variants can deal with this nonlinear problem effectively, they suffer from severe particle degeneracy and depletion, which leads to its sub-optimal performance. In this study, we combined the whale algorithm with regularized particle filtering(RPF) to rationalize the particle distribution before resampling, so as to solve the problem of particle degradation, and for valve RUL prediction. The valve's crack propagation is studied using the RPF approach, which takes the Paris Law as a condition function. The crack growth is observed and updated using the root-mean-square (RMS) signal collected from the acoustic emission sensor. At the same time, the proposed method is compared with other optimization algorithms, such as particle swarm optimization algorithm, and verified by the realistic valve aging experimental data. The conclusion shows that the proposed method can effectively predict and analyze the typical valve degradation patterns.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.658-675
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• 2022

This paper presents a fast-simplified successive cancellation (SC) flipping (Fast-SSC-Flip) decoding algorithm for polar code. Firstly, by researching the probability distribution of the number of error bits in a node caused by channel noise in simplified-SC (SSC) decoder, a measurement criterion of node reliability is proposed. Under the guidance of the criterion, the most unreliable nodes are firstly located, then the unreliable bits are selected for flipping, so as to realize Fast-SSC-Flip decoding algorithm based on node reliability (NR-Fast-SSC-Flip). Secondly, we extended the proposed NR-Fast-SSC-Flip to multiple node (NR-Fast-SSC-Flip-ω) by considering dynamic update to measure node reliability, where ω is the order of flip-nodes set. The extended algorithm can correct the error bits in multiple nodes, and get good performance at medium and high signal-to-noise (SNR) region. Simulation results show that the proposed NR-Fast-SSC-Flip decoder can obtain 0.27dB and 0.17dB gains, respectively, compared with the traditional Fast-SSC-Flip [14] and the newly proposed two-bit-flipping Fast-SSC (Fast-SSC-2Flip-E2) [18] under the same conditions. Compared with the newly proposed partitioned Fast-SSC-Flip (PA-Fast-SSC-Flip) (s=4) [18], the proposed NR-Fast-SSC-Flip-ω (ω=2) decoder can obtain about 0.21dB gain, and the FER performance exceeds the cyclic-redundancy-check (CRC) aided SC-list (CRC-SCL) decoder (L=4).

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.19-26
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• 2010

This paper proposes a classifier based on rectangular feature to detect face in real time. The goal is to realize a strong detection algorithm which satisfies both efficiency in calculation and detection performance. The proposed algorithm consists of the following three stages: Feature creation, classifier study and real time facial domain detection. Feature creation organizes a feature set with the proposed five rectangular features and calculates the feature values efficiently by using SAT (Summed-Area Tables). Classifier learning creates classifiers hierarchically by using the AdaBoost algorithm. In addition, it gets excellent detection performance by applying important face patterns repeatedly at the next level. Real time facial domain detection finds facial domains rapidly and efficiently through the classifier based on the rectangular feature that was created. Also, the recognition rate was improved by using the domain which detected a face domain as the input image and by using PCA and KNN algorithms and a Class to Class rather than the existing Point to Point technique.

• Journal of Power Electronics
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• v.18 no.3
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• pp.841-852
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• 2018

This paper presents a dual-algorithm search method (GWO-GSO) combining grey wolf optimization (GWO) and golden-section optimization (GSO) to realize maximum power point tracking (MPPT) for photovoltaic (PV) systems. First, a modified grey wolf optimization (MGWO) is activated for the global search. In conventional GWO, wolf leaders possess the same impact on decision-making. In this paper, the decision weights of wolf leaders are automatically adjusted with hunting progression, which is conducive to accelerating hunting. At the later stage, the algorithm is switched to GSO for the local search, which play a critical role in avoiding unnecessary search and reducing the tracking time. Additionally, a novel restart judgment based on the quasi-slope of the power-voltage curve is introduced to enhance the reliability of MPPT systems. Simulation and experiment results demonstrate that the proposed algorithm can track the global maximum power point (MPP) swiftly and reliably with higher accuracy under various conditions.