• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.187-192
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• 2023

With development of information technology and necessity for high security, using different identification methods has become very important. Each biometric feature has its own advantages and disadvantages and choosing each of them depends on our usage. Retinal scanning is a bio scale method for identification. The retina is composed of vessels and optical disk. The vessels distribution pattern is one the remarkable retinal identification methods. In this paper, a new approach is presented for identification via retinal images using LBP and hog methods. In the proposed method, it will be tried to separate the retinal vessels accurately via machine vision techniques which will have good sustainability in rotation and size change. HOG-based or LBP-based methods or their combination can be used for separation and also HSV color space can be used too. Having extracted the features, the similarity criteria can be used for identification. The implementation of proposed method and its comparison with one of the newly-presented methods in this area shows better performance of the proposed method.

• Korean Journal of Pharmacognosy
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• v.40 no.2
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• pp.155-160
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• 2009

The reference herbal extracts and their identification methods by Korean Pharmacopoeia IX were established based on the organic solvent extracts to detect their marker compounds. However, most of herbal medicine decoctions in the market are prepared with water as extracting solvent. As the reference herbal extracts and their identification methods are not appropriate for the practical test, new preparation of alternative reference herbal extracts and their identification test methods are essential for the correction of test methods and identification of herbal drugs. Three novel identification test methods were developed for Evodiae Fructus, Cimicifugae Rhizoma and Aurantii Fructus Immaturus. Total 10 reference herbal extracts and their identification methods were optimized for Ephedrae Herba, Schisandrae Fructus, Curcuma longae Rhizoma, Citri Unshius Pericarpium, Puerariae Radix, Corni Fructus, and Cinnamomi Cortex.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.445-466
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• 2004

In this paper, several modal identification techniques for output-only structural systems are extensively investigated. The methods considered are the power spectral method, the frequency domain decomposition method, the Ibrahim time domain method, the eigensystem realization algorithm, and the stochastic subspace identification method. Generally, the power spectral method is most widely used in practical area, however, the other methods may give better estimates particularly for the cases with closed modes and/or with large measurement noise. Example analyses were carried out on typical structural systems under three different loading cases, and the identification performances were examined throught the comparisons between the estimates by various methods.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.51-58
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• 2016

In the area of hotel and tourism sector, various research are analyzed using big data. Big data is being generated by any digital devices around us all the times. All the digital process and social media exchange produces the big data. In this paper, we analyzed the de-identification method of big data to use the personal information of hotel guests. Through the analysis of these big data, hotel can provide differentiated and diverse services to hotel guests and can improve the service and support the marketing of hotels. If the hotel wants to use the information of the guest, the private data should be de-identified. There are several de-identification methods of personal information such as pseudonymisation, aggregation, data reduction, data suppression and data masking. Using the comparison of these methods, the pseudonymisation is discriminated to the suitable methods for the analysis of information for the hotel guest. Also, among the pseudonymisation methods, the t-closeness was analyzed to the secure and efficient method for the de-identification of personal information in hotel.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.1-34
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• 2016

Gene identification is at the center of genomic studies. Although the first phase of the Encyclopedia of DNA Elements (ENCODE) project has been claimed to be complete, the annotation of the functional elements is far from being so. Computational methods in gene identification continue to play important roles in this area and other relevant issues. So far, a lot of work has been performed on this area, and a plethora of computational methods and avenues have been developed. Many review papers have summarized these methods and other related work. However, most of them focus on the methodologies from a particular aspect or perspective. Different from these existing bodies of research, this paper aims to comprehensively summarize the mainstream computational methods in gene identification and tries to provide a short but concise technical reference for future studies. Moreover, this review sheds light on the emerging trends and cutting-edge techniques that are believed to be capable of leading the research on this field in the future.

• BMB Reports
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• v.45 no.10
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• pp.545-553
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• 2012

Determination of the type and origin of the body fluids found at a crime scene can give important insights into crime scene reconstruction by supporting a link between sample donors and actual criminal acts. For more than a century, numerous types of body fluid identification methods have been developed, such as chemical tests, immunological tests, protein catalytic activity tests, spectroscopic methods and microscopy. However, these conventional body fluid identification methods are mostly presumptive, and are carried out for only one body fluid at a time. Therefore, the use of a molecular genetics-based approach using RNA profiling or DNA methylation detection has been recently proposed to supplant conventional body fluid identification methods. Several RNA markers and tDMRs (tissue-specific differentially methylated regions) which are specific to forensically relevant body fluids have been identified, and their specificities and sensitivities have been tested using various samples. In this review, we provide an overview of the present knowledge and the most recent developments in forensic body fluid identification and discuss its possible practical application to forensic casework.

• Computational Structural Engineering : An International Journal
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• v.3 no.1
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• pp.1-7
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• 2003

For system identification of large structures, it is not practical to identify the entire structure due to the prohibitive computational time and difficulty in numerical convergence. This paper explores the possibility of performing system identification at substructure level, taking advantage of reduction in both the number of unknowns and the number of degrees of freedom involved. Another advantage is that different portions (substructures) of a structural system can be identified independently and even concurrently with parallel computing. Two substructural identification methods are formulated on the basis whether substructural approach is used to obtain first-order or second-order model. For substructural first-order model, identification at the substructure level will be performed by means of the Observer/Kalman filter Identification (OKID) and the Eigensystem Realization Algorithm (ERA) whereas identification at the global level will be performed to obtain second-order model in order to evaluate the system's stiffness and mass parameters. In the case of substructural second-order model, identification will be performed at the substructure level throughout the identification process. The efficiency of the proposed technique is shown by numerical examples for multi-storey shear buildings subjected to random forces, taking into consideration the effects of noisy measurement data. The results indicate that both the proposed methods are effective and efficient for damage identification of large structures.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.433-439
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• 1998

In this paper, we present an approach to the structure identification based on the input space partition methods and to the parameter identification by hybrid learning method in neuro-fuzzy system. The structure identification can automatically estimate the number of membership function and fuzzy rule using grid partition, tree partition, scatter partition from numerical input-output data. And then the parameter identification is carried out by the hybrid learning scheme using back-propagation and least squares estimate. Finally, we sill show its usefulness for neuro-fuzzy modeling to truck backer-upper control.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.345-351
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• 2021

This study is designed to determine how to identify misleading news articles based on natural language processing on Artificial Intelligence & Bigdata. A misleading news discrimination system and method on natural language processing is initiated according to an embodiment of this study. The natural language processing-based misleading news identification system, which monitors the misleading vocabulary database, Internet news articles, collects misleading news articles, extracts them from the titles of the collected misleading news articles, and stores them in the misleading vocabulary database. Therefore, the use of the misleading news article identification system and methods in this study does not take much time to judge because only relatively short news titles are morphed analyzed, and the use of a misleading vocabulary database provides an effect on identifying misleading articles that attract readers with exaggerated or suggestive phrases. For the aim of our study, we propose news article identification methods in natural language processing on Artificial Intelligence & Bigdata.

• Structural Engineering and Mechanics
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• v.78 no.3
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• pp.369-378
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• 2021

This paper reviewed a few output-only system identification algorithms and identified the shortcomings of those popular blind source separation methods. To address the issues such as less sensors than the targeted modal modes (under-determinate problem), repeated natural frequencies as well as systems with complex mode shapes, this paper proposed a complex wavelet modified second order blind identification method (CWMSOBI) by transforming the time domain problem into time-frequency domain. The wavelet coefficients with different dominant frequencies can be used to address the under-determinate problem, while complex mode shapes are addressed by introducing the complex wavelet transformation. Numerical simulations with both high and low signal-to-noise ratios validate that CWMSOBI can overcome the above-mentioned issues while obtaining more accurate identified results than other blind identification methods.