• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.551-555
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• 2010

In protein 2-DE image analysis, the accuracy of spot-matching operation which identifies the spot of the same protein in each 2-DE gel image is intensively influenced by the errors caused by the various experimental conditions. This paper proposes an efficient method to find more accurate spot-matching patterns based on multiple reference gel images in spot-matching pattern analysis in protein 2-DE image analysis. Additionally, in order to improve the reduce the execution time which is increased exponentially along with the increasing number of gel images, a "partition then extension" framework is used to find spot-matching pattern of long length and of higher accuracy. In the experiments on real 2-DE images of human liver tissue are used to confirm the accuracy and the efficiency of the proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.145-153
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• 2020

Recently, keyword extraction from social big data has been widely used for the purpose of extracting opinions or complaints from the user's perspective. Regarding this, our previous work suggested a method to improve accuracy of keyword extraction based on the notion of cohesion scoring, but its accuracy can be degraded when the number of input reviews is relatively small. This paper presents a method to resolve this issue by applying simplified morphological analysis as a postprocessing step to extracted keywords generated from the algorithm discussed in the previous work. The proposed method enables to add analysis rules necessary to process input data incrementally whenever new data arrives, which leads to reduction of a dictionary size and improvement of analysis efficiency. In addition, an interactive rule adder is provided to minimize efforts to add new rules. To verify performance of the proposed method, experiments were conducted based on real social reviews collected from online, where the results showed that error ratio was reduced from 10% to 1% by applying our method and it took 450 milliseconds to process 5,000 reviews, which means that keyword extraction can be performed in a timely manner in the proposed method.

• Earthquakes and Structures
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• v.22 no.3
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• pp.245-261
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• 2022

Key questions to researchers interested in nonlinear analysis of skeletal structures are whether the distributed plasticity approach - albeit computationally demanding - is more reliable than the concentrated plasticity to adequately capture the extent and severity of the inelastic response, and whether force-based formulation is more efficient than displacement-based formulation without compromising accuracy. The present research focusing on performance-based seismic response of mid-span concrete bridges provides a pilot holistic investigation opting for some hands-on answers. OpenSees software is considered adopting different modeling techniques, viz. distributed plasticity (through either displacement-based or force-based elements) and concentrated plasticity via beam-with-hinges elements. The pros and cons of each are discussed based on nonlinear pushover analysis results, and fragility curves generated for various performance levels relying on incremental dynamic analyses under real earthquake records. Among prime conclusions, distributed plasticity modeling albeit inherently not relying on prior knowledge of plastic hinge length still somewhat depends on such information to ensure accurate results. For instance, displacement-based and force-based approaches secure optimal accuracy when dividing, for the former, the member into sub-elements, and satisfying, for the latter, a distance between any two consecutive integration points, close to the expected plastic hinge length. On the other hand, using beam-with-hinges elements is computationally more efficient relative to the distributed plasticity, yet with acceptable accuracy provided the user has prior reasonable estimate of the anticipated plastic hinge length. Furthermore, when intrusive performance levels (viz. life safety or collapse) are of concern, concentrated plasticity via beam-with-hinges ensures conservative predicted capacity of investigated bridge systems.

• Progress in Medical Physics
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• v.34 no.3
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• pp.23-32
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• 2023

Purpose: In radiomics analysis, to evaluate features, and predict genetic characteristics and survival time, the pixel values of lesions depicted in computed tomography (CT) and magnetic resonance imaging (MRI) images are used. CT and MRI offer three-dimensional images, thus producing three-dimensional features (Features_3d) as output. However, in reports, the superiority between Features_3d and two-dimensional features (Features_2d) is distinct. In this study, we aimed to investigate whether a difference exists in the prediction accuracy of radiomics analysis of lung cancer using Features_2d and Features_3d. Methods: A total of 38 cases of large cell carcinoma (LCC) and 40 cases of squamous cell carcinoma (SCC) were selected for this study. Two- and three-dimensional lesion segmentations were performed. A total of 774 features were obtained. Using least absolute shrinkage and selection operator regression, seven Features_2d and six Features_3d were obtained. Results: Linear discriminant analysis revealed that the sensitivities of Features_2d and Features_3d to LCC were 86.8% and 89.5%, respectively. The coefficients of determination through multiple regression analysis and the areas under the receiver operating characteristic curve (AUC) were 0.68 and 0.70 and 0.93 and 0.94, respectively. The P-value of the estimated AUC was 0.87. Conclusions: No difference was found in the prediction accuracy for LCC and SCC between Features_2d and Features_3d.

• Korean Journal of Radiology
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• v.23 no.3
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• pp.295-297
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• 2022

• Progress in Medical Physics
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• v.14 no.3
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• pp.189-195
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• 2003

The comparative analysis of a portal image and a simulation image is a very important process in radiotherapy for verifying the accuracy of an actual treatment field. In this study, we applied a chamfer-matching algorithm to compare a portal image with a simulation image and verified the accuracy of the algorithm to analyze the field matching error in the portal image. We also developed an analysis program that could analyze the two images more effectively with a chamfer-matching method and demonstrated its efficacy through a feasibility study. With virtual portal images, the accuracy of the analysis algorithm were acceptable considering the average error of shift (0.64 mm), rotation (0.32$^{\circ}$), and scale (1.61%). When the portal images of a head and neck phantom were analyzed, the accuracy and suitability of the developed analysis program was proven considering the acceptable average error of shift (1.55 mm), rotation (0.80$^{\circ}$), and scale (1.72%). We verified the applicability of a chamfer-matching algorithm to the comparative analysis of a portal image with a simulation image. The analysis program developed in this study was a practical tool to calculate the quantitative error of the treatment field in a portal image.

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.3
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• pp.237-245
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• 2004

In designing a tunnel, RMR has been widely used to classify rock mass and to decide the support pattern according to the class of rock mass. However, this RMS system can't help relying on the empirical judgment of engineers who use variables which can be obtained only through consideration of the site conditions. In actuality, it is impossible to consider all the rating factors of RMS when using RMR system at the stage of designing. Therefore, in order to confirm possibility of RMR by use of only the quantitative factors for designing, this paper has done discriminant analysis. Rock strength or RQD has high coefficient of correlation with RMR value, and in consideration of the existing standards for rock mass classification, rock intensity and RQD are important factors for classification of rock mass. Through rock mass classification by the existing RMR system and rock mass classification by the discriminant analysis which has considered two variables only, the discriminant analysis using the rock intensity as an independent variable has shown 74.8% accuracy while the discriminant analysis using RQD as an independent variable has shown 74.3% accuracy. In case of the discriminant analysis which has considered both rock intensity and RQD, it has shown 82.5% accuracy. The existing cases have shown 40.3% accuracy at the stage of designing in which all the RMR factors are considered. It means that at the stage of designing, RMR system can work only with the rock intensity and RQD.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.492-499
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• 2022

This study experimentally investigates the effect of dimensionality reduction of vibration signal on fault diagnosis of a marine engine. By using the principal component analysis, a vibration signal having the dimension of 513 is converted into a low-dimensional signal having the dimension of 1 to 15, and the variation in fault diagnosis accuracy according to the dimensionality change is observed. The vibration signal measured from a full-scale marine generator diesel engine is used, and the contribution of the dimension-reduced signal is quantitatively evaluated using two kinds of variable importance analysis algorithms which are the integrated gradients and the feature permutation methods. As a result of experimental data analysis, the accuracy of the fault diagnosis is shown to improve as the number of dimensions used increases, and when the dimension approaches 10, near-perfect fault classification accuracy is achieved. This shows that the dimension of the vibration signal can be considerably reduced without degrading fault diagnosis accuracy. In the variable importance analysis, the dimension-reduced principal components show higher contribution than the conventional statistical features, which supports the effectiveness of the dimension-reduced signals on fault diagnosis.

• Atmosphere
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• v.28 no.1
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• pp.99-112
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• 2018

In this study, the accuracy of ocean analysis data, which are produced from the Korea Meteorological Administration (KMA) Nucleus for European Modelling of the Ocean/Variational Data Assimilation (NEMO/NEMOVAR, hereafter NEMO) system and the HYbrid Coordinate Ocean Model/Navy Coupled Ocean Data Assimilation (HYCOM/NCODA, hereafter HYCOM) system, was evaluated using various oceanic observation data from March 2015 to February 2016. The evaluation was made for oceanic thermal environments in the tropical Pacific, the western North Pacific, and the Korean peninsula. NEMO generally outperformed HYCOM in the three regions. Particularly, in the tropical Pacific, the RMSEs (Root Mean Square Errors) of NEMO for both the sea surface temperature and vertical water temperature profile were about 50% smaller than those of HYCOM. In the western North Pacific, in which the observational data were not used for data assimilation, the RMSE of NEMO profiles up to 1000 m ($0.49^{\circ}C$) was much lower than that of HYCOM ($0.73^{\circ}C$). Around the Korean peninsula, the difference in RMSE between the two models was small (NEMO, $0.61^{\circ}C$; HYCOM, $0.72^{\circ}C$), in which their errors show relatively big in the winter and small in the summer. The differences reported here in the accuracy between NEMO and HYCOM for the thermal environments may be attributed to horizontal and vertical resolutions of the models, vertical coordinate and mixing scheme, data quality control system, data used for data assimilation, and atmosphere forcing. The present results can be used as a basic data to evaluate the accuracy of NEMO, before it becomes the operational model of the KMA providing real-time ocean analysis and prediction data.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.141-149
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• 2010

Three-dimensional geo-spatial information is important for the efficient use and management of the country and the three-dimensional expression and analysis of urban projects, such as urban plans devised by local governments and urban management. Thanks to the revitalization of the geo-spatial information service industry, it is now being variously used not only in public but also private areas. For the creation of high-guiltily three-dimensional geo-spatial information, emphasis should be placed on not only the quality of the source image and three-dimensional geo-spatial model but also the level of visualization, such as level of detail and texturing. However, in the case of existing three-dimensional geo-spatial information, its establishment process is complicated and its data are not updated frequently enough, as it uses ready-created digital maps. In addition, as it uses Ortho Images, the images exist Relief displacement. As a result, the visibility is low and the three-dimensional models of artificial features are simplified to reach LoD between 2 and 3, making the images look less realistic. Therefore, this paper, analyzed the quality of three-dimensional geo-spatial information created using the three-dimensional modeling technique were applied using Digital photogrammetry technique, using digital aerial photo images by an existing large-format digital camera and multi-looking camera. The analysis of the accuracy of visualization information of three-dimensional models showed that the source image alone, without other visualization information, secured the accuracy of 84% or more and that the establishment of three-dimensional spatial information carried out simultaneously with filming made it easier to gain the latest data. The analysis of the location accuracy of true Ortho images used in the work process showed that the location accuracy was better than the allowable horizontal position accuracy of 1:1,000 digital maps.