• ETRI Journal
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• v.21 no.4
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• pp.83-93
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• 1999

This paper examines the correlations between user characteristics and their perferences for two selected features of Web-based OPAC systems. User characteristics identified in this study were age, gender, educational status, computer skills and OPAC experience. Usability features included interaction styles, character and image on screen, browsing and navigating style, screen layout, and ease of learning, whereas availability features attended to availability of information, quality of information and up-to-date information. Individual variables and features are described, and the correlation between the variables and the features are explored using Pearson's correlation coefficient(r). Although based on a small-scale sample survey, a considerably large number of statistically significant correlations were found between the users' characteristics and the selected evaluation features of interactive Web-based OPACs. From these observations, it seems to be suitable to recommend that system designers should make a more considered appraisal of the users' demographic characteristics in the design of the new generation of OPAC such as in user-tailored interactive Web-based OPAC systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2424-2441
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• 2012

In this paper, we propose a fake iris detection method that combines the optical and textural features of the human eye. To extract the optical features, we used dual Purkinje images that were generated on the anterior cornea and the posterior lens surfaces based on an analytic model of the human eye's optical structure. To extract the textural features, we measured the amount of change in a given iris pattern (based on wavelet decomposition) with regard to the direction of illumination. This method performs the following two procedures over previous researches. First, in order to obtain the optical and textural features simultaneously, we used five illuminators. Second, in order to improve fake iris detection performance, we used a SVM (Support Vector Machine) to combine the optical and textural features. Through combining the features, problems of single feature based previous works could be solved. Experimental results showed that the EER (Equal Error Rate) was 0.133%.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.178-181
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• 2005

Support vector machines is a powerful learning algorithm and attempt to separate belonging to two given sets in N-dimensional real space by a nonlinear surface, often only implicitly dened by a kernel function. We described breast tissue images analyses using texture features from Haar wavelet transformed images to classify breast lesion of ductal organ Benign, DCIS and CA. The approach for creating a classifier is composed of 2 steps: feature extraction and classification. Therefore, in the feature extraction step, we extracted texture features from wavelet transformed images with $10{\times}$ magnification. In the classification step, we created four classifiers from each image of extracted features using SVM(Support Vector Machines). In this study, we conclude that the best classifier in histological sections of breast tissue in the texture features from second-level wavelet transformed images used in Polynomial function.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.468-488
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• 2016

The paper proposes a novel framework for 3D face verification using dimensionality reduction based on highly distinctive local features in the presence of illumination and expression variations. The histograms of efficient local descriptors are used to represent distinctively the facial images. For this purpose, different local descriptors are evaluated, Local Binary Patterns (LBP), Three-Patch Local Binary Patterns (TPLBP), Four-Patch Local Binary Patterns (FPLBP), Binarized Statistical Image Features (BSIF) and Local Phase Quantization (LPQ). Furthermore, experiments on the combinations of the four local descriptors at feature level using simply histograms concatenation are provided. The performance of the proposed approach is evaluated with different dimensionality reduction algorithms: Principal Component Analysis (PCA), Orthogonal Locality Preserving Projection (OLPP) and the combined PCA+EFM (Enhanced Fisher linear discriminate Model). Finally, multi-class Support Vector Machine (SVM) is used as a classifier to carry out the verification between imposters and customers. The proposed method has been tested on CASIA-3D face database and the experimental results show that our method achieves a high verification performance.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1326-1336
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• 2018

This paper proposes a numerical approach to predict the critical flashover voltages of air gaps under lightning impulses. For an air gap, the impulse voltage waveform features and electric field features are defined to characterize its energy storage status before the initiation of breakdown. These features are taken as the input parameters of the predictive model established by support vector machine (SVM). Given an applied voltage range, the golden section search method is used to compute the prediction results efficiently. This method was applied to predict the critical flashover voltages of rod-rod, rod-plane and sphere-plane gaps over a wide range of gap lengths and impulse voltage waveshapes. The predicted results coincide well with the experimental data, with the same trends and acceptable errors. The mean absolute percentage errors of 6 groups of test samples are within 4.6%, which demonstrates the validity and accuracy of the predictive model. This method provides an effectual way to obtain the critical flashover voltage and might be helpful to estimate the safe clearances of air gaps for insulation design.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.51-54
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• 2021

The article is devoted to the study of the features of administrative liability for offenses in the informational sphere, the definition of the concept and features. Based on the examples of implementation of instruments of European legislation into the national legal system and examples of national legal practice, the authors have identified the features of informational and legal sanctions aimed at restricting the rights of access of subjects to information, prohibiting them to disseminate certain information, restricting the rights to disseminate certain information, and suspending informational activities. It has been substantiated that the administrative liability for informational offenses as a protective legal institution is created to contribute to the solution of such acute problems of legal support of human and society interests in the new informational dimensions.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.43-53
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• 2014

Gunnery has been used to detect and classify artilleries. In this paper, we used electro-optical data to get the information of muzzle flash from the artilleries. Feature based approach was applied; we first defined features and sub-features. The number of sub-features was 38~40 generic sub-features, and 2 model-based sub-features. To classify multiclass data, we introduced tree structure with clustering the classes according to the similarity of them. SVM was used for each non-leaf nodes in the tree, as a sub-classifier. From the data, we extracted features and sub-features and classified them by the tree structure SVM classifier. The results showed that the performance of our classifier was good for our muzzle flash classification problem.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.667-674
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• 2004

Extraction of texts from images is a fundamental and important problem to understand the images. This paper suggests a text region verification method by statistical means of stroke features of the characters. The method extracts 36 dimensional features from $16\times16$sized text and non-text images using wavelet transform - these 36 dimensional features express stroke and direction of characters - and select 12 sub-features out of 36 dimensional features which yield adequate separation between classes. After selecting the features, SVM trains the selected features. For the verification of the text region, each $16\times16$image block is scanned and classified as text or non-text. Then, the text region is finally decided as text region or non-text region. The proposed method is able to verify text regions which can hardly be distin guished.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.263-266
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• 2009

Comments are short and not use spacing words or comma more than general document. We convert the 7-gram into 3-gram and select key features using topic signature. Topic signature is widely used for selecting features in document classification and summarization. We use the SVM(Support Vector Machines) as a classifier. From the result of experiments, we can see that the proposed method is outstanding over the previous methods. The proposed system can also apply to other languages.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.29-34
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• 2022

The innovative process of digitalization and creation of innovation from an idea to its commercialization requires certain financial costs, labor and mental efforts. The amount of investment (corporate and public) is the most important imperative to enhance innovation and is traditionally considered as the main "input" indicators of the development of innovation infrastructure, in this case, the financial infrastructure of innovation. At the same time, the modern theory of innovation development assumes a systematic approach to the organization of innovation activity, which provides for the close interaction of several subsystems: human (including intellectual) potential, financial and technological capital, as well as relevant institutions and methods of regulation.. Thus, the main task of the study is to analyze the features of investment support for the process of digitalization of socio-economic systems in the context of strengthening international economic relations. As a result of the study, current trends and prerequisites of investment support for the process of digitalization of socio-economic systems in the context of strengthening international economic relations were revealed.