• Journal of Korean Society of Transportation
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• v.31 no.4
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• pp.85-94
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• 2013

The Continuous Risk Profile (CRP) has been well known to be the most accurate and efficient among existing network screening methods. However, the classical CRP uses safety performance functions (SPFs) which require a huge investment to construct a database system. This study aims to suggest a new CRP method using average crash frequencies of homogeneous groups, instead of SPFs, as rescaling factors. Hierarchical clustering analysis is performed to classify freeway segments into homogeneous groups based on the data of AADT and number of lanes. Using the data from I-880 in California, the proposed method is compared to other several network screening methods. The results show that the proposed method decrease false positive rates while it does not produce any false negatives. The method developed in this study can be easily applied to screen freeway networks without any additional complex database systems, and contribute to the improvement of freeway safety management systems.

• The Journal of the Acoustical Society of Korea
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• v.23 no.7
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• pp.532-539
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• 2004

In this Paper, we propose a content-based music information retrieval (MIR) system base on the query-by-example (QBE) method. The proposed system is implemented to retrieve queried music from a dataset where 60 music samples were collected for each of the four genres in Classical, Hiphop. Jazz. and Reck. resulting in 240 music files in database. From each query music signal, the system extracts 60 dimensional feature vectors including spectral centroid. rolloff. flux base on STFT and also the LPC. MFCC and Beat information. and retrieves queried music from a trained database set using Euclidean distance measure. In order to choose optimum features from the 60 dimension feature vectors, SFS method is applied to draw 10 dimension optimum features and these are used for the Proposed system. From the experimental result. we can verify the superior performance of the proposed system that provides success rate of 84% in Hit Rate and 0.63 in MRR which means near 10% improvements over the previous methods. Additional experiments regarding system Performance to random query Patterns (or portions) and query lengths have been investigated and a serious instability problem of system Performance is Pointed out.

• Ocean and Polar Research
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• v.43 no.1
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• pp.45-51
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• 2021

Studies on marine zooplankton diversity and ecology are important for understanding marine ecosystem, as well as environmental conservation and fisheries management. DNA metabarcoding is known as a useful tool to reveal and understand diversity among animals, but a comparative evaluation with classical microscopy is still required in order to properly use it for marine zooplankton research. This study compared crustacean mesozooplankton taxa revealed by morphological analysis and metabarcoding of the cytochrome oxidase I (COI). A total of 17 crustacean species were identified by morphological analysis, and 18 species by metabarcoding. Copepods made up the highest proportion of taxa, accounting for more than 50% of the total number of species delineated by both methods. Cladocerans were not found by morphological analysis, whereas amphipods and mysids were not detected by metabarcoding. Unlike morphological analysis, metabarcoding was able to identify decapods down to the species level. There were some discrepancies in copepod species, which could be due to a lack of genetic database, or biases during DNA extraction, amplification, pooling and bioinformatics. Morphological analysis will be useful for ecological studies as it can classify and quantify the life history stages of marine zooplankton that metabarcoding cannot detect. Metabarcoding can be a powerful tool for determining marine zooplankton diversity, if its methods or database are further supplemented.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1423-1430
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• 2017

Detonation cell width is an important parameter in hydrogen explosion assessments. The experimental data on gas detonation are statistically analyzed to establish a universal method to numerically predict detonation cell widths. It is commonly understood that detonation cell width, ${\lambda}$, is highly correlated with the characteristic reaction zone width, ${\delta}$. Classical parametric regression methods were widely applied in earlier research to build an explicit semiempirical correlation for the ratio of ${\lambda}/{\delta}$. The obtained correlations formulate the dependency of the ratio ${\lambda}/{\delta}$ on a dimensionless effective chemical activation energy and a dimensionless temperature of the gas mixture. In this paper, support vector regression (SVR), which is based on nonparametric machine learning, is applied to achieve functions with better fitness to experimental data and more accurate predictions. Furthermore, a third parameter, dimensionless pressure, is considered as an additional independent variable. It is found that three-parameter SVR can significantly improve the performance of the fitting function. Meanwhile, SVR also provides better adaptability and the model functions can be easily renewed when experimental database is updated or new regression parameters are considered.

• Journal of Acupuncture Research
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• v.26 no.2
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• pp.147-158
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• 2009

Objectives : The purpose of this study is to review the recent research trends of evidence based medicine, especially human randomized controlled trials on acupuncture. Methods : The articles were collected by retrieving the database of Pubmed and Journal of Korean Acupuncture & Moxibustion Society. The retrieving period was from October 2003 to September 2008, and the search term was 'acupuncture'. The articles were classified according to their publication journals, countries, publication years, targeted diseases, types of acupuncture and types of control. Results : In total, 558 articles in Pubmed and 35 articles in Journal of Korean Acupuncture & Moxibustion Society were searched. The number of articles on acupuncture research has increased with higher rate since 2000, but the Qualitative development has not achieved the same amplitude. Studies in Korea were insufficient both in Qualitative and Quantitative aspects. In countries, China had the most papers, and in targeted diseases, pain diseases were most dominant. In the types of acupuncture, classical acupuncture, and in the types of control, conventional western treatment showed the highest frequency. Conclusions: We need to do many-sided and more high Quality researches on acupuncture. For that, well-designed randornized trials are absolutely necessary.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.3
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• pp.361-368
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• 2012

This paper presents an approach on the design of a nonlinear controller to track a reference velocity for an air-breathing supersonic vehicle. The nonlinear control scheme involves an adaptation of propulsive and aerodynamic characteristics in the equations of motion. In this paper, the coefficients of given thrust and drag functions are estimated and they are used to approximate the equations of motion under varying flight conditions. The form of the function of propulsive thrust is extracted from a thrust database which is given by preliminary engine input/output performance analysis. The aerodynamic drag is approximated as a function of angle of attack and fin deflection. The nonlinear controller, designed by using the approximated nonlinear control model equations, provides engine fuel supply command to follow the desired velocity varying with time. On the other hand, the stabilization of altitude, separated from the velocity control scheme, is done by a classical altitude hold autopilot design. Finally, several simulations are performed in order to demonstrate the relevance of the controller design regarding the vehicle.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.673-675
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• 2005

The art psychotherapy expert system is a computer system which helps to analyse one's psychology through pictures. However we need a standard criterion because the psychology, the target of the art psychotherapy, does not only have a ambiguous criterion but also a vast range. We're going to suggest a criterion in the field of the art psychotherapy by constructing systematic database through knowledge acquirement of the art psychotherapy expert system. In this study we introduce a system which enables systematic classification and confirmation of symptoms according to mental analyses. The suggested system enables confirmation of a classical structure and systematic classification of knowledges through conversation by extracting nouns through sentence analysis from the knowledge of descriptive form based on the clinical purpose of sentence analysis.

• Computers and Concrete
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• v.12 no.2
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• pp.187-209
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• 2013

This paper presents a study on the prediction of transfer length of 13 mm seven-wire prestressing steel strand in pretensioned prestressed concrete members with rectangular cross-section including several material properties and design and manufacture parameters. To this end, a carefully selected database consisting of 207 different cases coming from 18 different sources spanning a variety of practical transfer length prediction situations was compiled. 16 single input features and 5 combined input features are analyzed. A widely used feedforward neural regression model was considered as a representative of several machine learning methods that have already been used in the engineering field. Classical multiple linear regression was also considered in order to comparatively assess performance and robustness in this context. The results show that the implemented model has good prediction and generalization capacity when it is used on large input data sets of practical interest from the engineering point of view. In particular, a neural model is proposed -using only 4 hidden units and 10 input variables-which significantly reduces in 30% and 60% the errors in transfer length prediction when using standard linear regression or fixed formulas, respectively.

• International Journal of Contents
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• v.6 no.1
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• pp.59-64
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• 2010

Recently, biological researches are required to deal with a large scale of data. While scientists used classical experimental approaches for researches in the past, it is possible to get more sophisticated observations easily with the convergence of information technologies and biology. The study on diseases is one of the most important issues of the life science. Conventional services and databases provide users with information such as classification of diseases, symptoms, and medical treatments through the Web. However, it is hard to connect or develop them for other new services because they have independent and different criteria. It may be a factor that interferes the development of biology. In this paper, we propose integrated data structures for the disease databases. We also design and implement a novel directory system for diseases as an infrastructure for developing the new diseases services.