• 대한의생명과학회지
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• 제15권3호
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• pp.187-197
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• 2009

Fingerprinting is a frontier technique that is the most frequently applied for human identification throughout the world. All citizens over 17 year old living in the Republic of Korea must be fingerprinted to obtain a certificate of resident registration. In Korea, for this reason, human identification through fingerprints has been far better developed and used efficiently both in crime scene investigation and in confirmation of an unidentified body. Scientific approaches have been made to accurately extract the metamorphosed fingerprints in various environments. Because most of the studies on fingerprinting have been accomplished with biometric techniques, researches on restoration of human dermal tissue and taking custody data after collecting fingerprints have been comparatively undermined. In this study, a newly innovative method for fingerprint extraction was developed using the polyester film with print powders and the high temperature-moisturizing method. Compared to the conventional fingerprinting method of paper with ink, minutiae numbers of fingerprints were greatly increased in polyester film with print powders after restoration of fingertips by high temperature-moisturization. This newly developed procedure would be an efficient fingerprinting technique which could be utilized in scientific investigation and in personal identification in the future. Furthermore, the new method for restoration and extraction of fingerprints are easy and inexpensive to practice for a number of human identification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.2294-2309
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• 2020

In this article, a new Aloha-based tag identification protocol is presented to improve the reading efficiency of the EPC C1 Gen2-based UHF RFID system. Collision detection (CD) plays a vital role in tag identification process which determines the efficiency of anti-collision protocols since most Aloha-based protocols optimize the incoming frame length based on the collisions in current frame. Existing CD methods are ineffective in identifying collision, resulting in a degradation of identification performance. Our proposed algorithm adopts an enhanced CD (ECD) scheme based on the EPC C1 Gen2 standard to optimize identification performance. The ECD method can realize timely and effective CD by detecting the pulse width of the randomly sent by tags. According to the ECD, the reader detects the slot distribution and predicts tag cardinality in every collision slot. The tags involved in each collision slot are identified by independently assigned sub-frames. A large number of numerical results show that the proposed solution is superior to other existing anti-collision protocols in various performance evaluation metrics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.5087-5102
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• 2015

Rapid popularization of smart cell phone equipped with camera has led to a number of new legal and criminal problems related to multimedia such as digital image, which makes cell phone source identification an important branch of digital image forensics. This paper proposes a classifier combination based source identification strategy for cell phone images. To identify the outlier cell phone models of the training sets in multi-class classifier, a one-class classifier is orderly used in the framework. Feature vectors including color filter array (CFA) interpolation coefficients estimation and multi-feature fusion is employed to verify the effectiveness of the classifier combination strategy. Experimental results demonstrate that for different feature sets, our method presents high accuracy of source identification both for the cell phone in the training sets and the outliers.

• 한국화재소방학회논문지
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• 제24권3호
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• pp.78-85
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• 2010

현재 화재조사 및 감식을 하는 기관은 소방, 경찰을 비롯하여 화재안전관련 기관 등으로 다양하며 이에 종사하는 인력들도 상당수에 이르고 있으나 이들의 전문성에 대한 어떠한 객관적인 지표가 없는 것이 현실이다. 본 연구에서는 직무분석을 통하여 검정기준을 마련, 시험제도의 시행방안을 제시하였고, 화재감식 평가 자격에 적합한 검정과목과 출제기준을 개발하여 화재현장에서 발화원인, 연소상황, 피난상황, 소방시설 등의 상황을 조사하고, 화재피해조사, 화재 분석 및 평가 등의 업무를 수행할 수 있는 공신력 있는 화재감식평가기사 국가기술자격 종목을 개발하고자 한다.

• Smart Structures and Systems
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• 제15권3호
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• pp.787-806
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• 2015

Due to corrosion, a large number of belt conveyors support structure in industrial plants have deteriorated. Severe corrosion may result in collapse of the structures. Therefore, practical and effective structural assessment techniques are needed. In this paper, damage identification methods based on two specific local vibration modes, named periodic and isolated local vibration modes, are proposed. The identification methods utilize the facts that support structures have many identical members repeated along the belt conveyor and there exist some local modes within a small frequency range where vibrations of these identical members are much larger than those of the other members. When one of these identical members is damaged, this member no longer vibrates in those modes. Instead, the member vibrates alone in an isolated mode with a lower frequency. A damage identification method based on frequencies comparison of these vibration modes and another method based on amplitude comparison of the periodic local vibration mode are explained. These methods do not require the baseline measurement records of undamaged structure. The methods is capable of detecting multiple damages simultaneously. The applicability of the methods is experimentally validated with a laboratory model and a real belt-conveyor support structure.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.394-399
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• 2005

In this paper, a structural damage identification method (SDIM) is developed to identify the line crack-like directional damages generated within a cylindrical shell. First, the equations of motion fur a damaged cylindrical shell are derived. Based on a theory of continuum damage mechanics, a small material volume containing a directional damage is represented by the effective orthotropic elastic stiffness, which is dependent of the size and the orientation of the damage with respect to the global coordinates. The present SDIM is then derived from the frequency response function (FRF) directly solved from the dynamic equations of the damaged cylindrical shell. In contrast with most existing SDIMs which require the modal parameters measured in both intact and damaged states, the present SDIM requires only the FRF-data measured in damaged state. By virtue of utilizing FRF-data, one may choose as many sets of excitation frequency and FRF measurement point as needed to acquire a sufficient number of equations fer damage identification analysis. The numerically simulated damage identification tests are conducted to study the feasibility of the present SDIM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권6호
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• pp.3055-3073
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• 2019

In this paper, a new user identification method is presented using real environmental human-computer-interaction (HCI) behavior data to improve method usability. User behavior data in this paper are collected continuously without setting experimental scenes such as text length, action number, etc. To illustrate the characteristics of real environmental HCI data, probability density distribution and performance of keyboard and mouse data are analyzed through the random sampling method and Support Vector Machine(SVM) algorithm. Based on the analysis of HCI behavior data in a real environment, the Multiple Kernel Learning (MKL) method is first used for user HCI behavior identification due to the heterogeneity of keyboard and mouse data. All possible kernel methods are compared to determine the MKL algorithm's parameters to ensure the robustness of the algorithm. Data analysis results show that keyboard data have a narrower range of probability density distribution than mouse data. Keyboard data have better performance with a 1-min time window, while that of mouse data is achieved with a 10-min time window. Finally, experiments using the MKL algorithm with three global polynomial kernels and ten local Gaussian kernels achieve a user identification accuracy of 83.03% in a real environmental HCI dataset, which demonstrates that the proposed method achieves an encouraging performance.

• 한국멀티미디어학회논문지
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• 제22권6호
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• pp.655-664
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• 2019

In this paper, we propose a novel way of combining multiple deep convolutional neural network (DCNN) architectures which work well for accurate video face identification by adopting a serial combination of 3D and 2D DCNNs. The proposed method first divides an input video sequence (to be recognized) into a number of sub-video sequences. The resulting sub-video sequences are used as input to the 3D DCNN so as to obtain the class-confidence scores for a given input video sequence by considering both temporal and spatial face feature characteristics of input video sequence. The class-confidence scores obtained from corresponding sub-video sequences is combined by forming our proposed class-confidence matrix. The resulting class-confidence matrix is then used as an input for learning 2D DCNN learning which is serially linked to 3D DCNN. Finally, fine-tuned, serially combined DCNN framework is applied for recognizing the identity present in a given test video sequence. To verify the effectiveness of our proposed method, extensive and comparative experiments have been conducted to evaluate our method on COX face databases with their standard face identification protocols. Experimental results showed that our method can achieve better or comparable identification rate compared to other state-of-the-art video FR methods.

• Nuclear Engineering and Technology
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• 제53권6호
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• pp.2038-2045
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• 2021

The main objective of this work is to propose a reliable routine standard operation procedures (SOP) for structural health monitoring and diagnosis of nuclear power plants (NPPs). At present, NPPs have monitoring systems that can be used to obtain the quantitative health record of containment (CTMT) buildings through system identification technology. However, because the measurement signals are often interfered with by noise, the identification results may introduce erroneous conclusions if the measured data is directly adopted. Therefore, this paper recommends the SOP for signal screening and the required identification procedures to identify the dynamic characteristics of the CTMT of NPPs. In the SOP, three recommend methods are proposed including the Recursive Least Squares (RLS), the Observer Kalman Filter Identification/Eigensystem Realization Algorithm (OKID/ERA), and the Frequency Response Function (FRF). The identification results can be verified by comparing the results of different methods. Finally, a preliminary CTMT healthy record can be established based on the limited number of earthquake records. It can be served as the quantitative reference to expedite the restart procedure. If the fundamental frequency of the CTMT drops significantly after the Operating Basis Earthquake and Safe Shutdown Earthquake (OBE/SSE), it means that the restart actions suggested by the regulatory guide should be taken in place immediately.

• 음성과학
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• 제10권4호
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• pp.117-124
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• 2003

Speaker recognition is the technology that confirms the identification of speaker by using the characteristic of speech. Such technique is classified into speaker identification and speaker verification: The first method discriminates the speaker from the preregistered group and recognize the word, the second verifies the speaker who claims the identification. This method that extracts the information of speaker from the speech and confirms the individual identification becomes one of the most efficient technology as the service via telephone network is popularized. Some problems, however, must be solved for the real application as follows; The first thing is concerning that the safe method is necessary to reject the imposter because the recognition is not performed for the only preregistered customer. The second thing is about the fact that the characteristic of speech is changed as time goes by, So this fact causes the severe degradation of recognition rate and the inconvenience of users as the number of times to utter the text increases. The last thing is relating to the fact that the common characteristic among speakers causes the wrong recognition result. The silence parts being included the center of speech cause that identification rate is decreased. In this paper, to make improvement, We proposed identification rate can be improved by removing silence part before processing identification algorithm. The methods detecting speech area are zero crossing rate, energy of signal detect end point and starting point of the speech and process DTW algorithm by using two methods in this paper. As a result, the proposed method is obtained about 3% of improved recognition rate compare with the conventional methods.