• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.633-641
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• 2009

In this paper, we proposed a new pattern classifier which can be incrementally learned, be added new class in learning time, and handle with analog data. Proposed pattern classifier has hierarchical structure and the classification rate is improved by using different metric for each levels. Proposed model is based on the Gaussian ARTMAP which is an artificial neural network model for the pattern classification. We hierarchically constructed the Gaussian ARTMAP and proposed the Principal Component Emphasis(P.C.E) method to be learned different features in each levels. And we defined new metric based on the P.C.E. P.C.E is a method that discards dimensions whose variation are small, that represents common attributes in the class. And remains dimensions whose variation are large. In the learning process, if input pattern is misclassified, P.C.E are performed and the modified pattern is learned in sub network. Experimental results indicate that Hierarchical Gaussian ARTMAP yield better classification result than the other pattern recognition algorithms on variable data set including real applicable problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.288-307
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• 2016

Image distortions are typically characterized by degradations of structures. Dictionaries learned from natural images can capture the underlying structures in images, which are important for image quality assessment (IQA). This paper presents a general-purpose no-reference image quality metric using a GRadient-Induced Dictionary (GRID). A dictionary is first constructed based on gradients of natural images using K-means clustering. Then image features are extracted using the dictionary based on Euclidean-norm coding and max-pooling. A distortion classification model and several distortion-specific quality regression models are trained using the support vector machine (SVM) by combining image features with distortion types and subjective scores, respectively. To evaluate the quality of a test image, the distortion classification model is used to determine the probabilities that the image belongs to different kinds of distortions, while the regression models are used to predict the corresponding distortion-specific quality scores. Finally, an overall quality score is computed as the probability-weighted distortion-specific quality scores. The proposed metric can evaluate image quality accurately and efficiently using a small dictionary. The performance of the proposed method is verified on public image quality databases. Experimental results demonstrate that the proposed metric can generate quality scores highly consistent with human perception, and it outperforms the state-of-the-arts.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.117-126
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• 2010

Software complexity is used to evaluate a target system's maintainability. The existing complexity metrics on web applications are count-based, so it is hard to incorporate the understandability of developers or maintainers. To make up for this shortcomings, entropy-theory can be applied to define complexity, however, it is assumed that information quantity of each paper is identical. In this paper, structural complexity of a web application is defined based on information theory and similarity. In detail, the proposed complexity is defined using entropy as the previous approach, but the information quantity of individual pages is defined using similarity. That is, a page which are similar with many pages has smaller information quantity than a page which are dissimilar to others. Furthermore, various similarity measures can be used for various views, which results in many-sided complexity measures. Finally, several complexity properties are applied to verify the proposed metric and case studies shows the applicability of the metric.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.95-105
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• 2018

As the IT industry developed, the information held by the company soon became a corporate asset. As this information has value as an asset, the number and scale of various cyber attacks which targeting enterprises and institutions is increasing day by day. Therefore, research are being carried out to protect the assets from cyber attacks by using the attack graph to identify the possibility and risk of various attacks in advance and prepare countermeasures against the attacks. In the attack graph, security metric is used as a measure for determining the importance of each asset or the risk of an attack. This is a key element of the attack graph used as a criterion for determining which assets should be protected first or which attack path should be removed first. In this survey, we research trends of various security metrics used in attack graphs and classify the research according to application viewpoints, use of CVSS(Common Vulnerability Scoring System), and detail metrics. Furthermore, we discussed how to graft the latest security technologies, such as MTD(Moving Target Defense) or SDN(Software Defined Network), onto the attack graphs.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.79-86
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• 2016

Under the influence of software security-enhanced development guidelines announced in 2012, secure coding practices become widely applicable in developing information systems aiming to enhance security capabilities. Although continuous enhancement activities for code security is important, management issues for code security have been less addressed in the guidelines. This paper analyses limitation of secure coding practices from the viewpoint of quality management. In particular this paper suggests structures and the use of software metrics from coding to maintenance phases so that it can be of help in the future by extending the use of security metrics.

• Journal of Navigation and Port Research
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• v.36 no.5
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• pp.363-370
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• 2012

Recently, International Maritime Organization has been developing e-navigation implementation strategy plan, which is focused on various services for vessel safety navigation. Then, different kinds of software will be developed in maritime area and with this, the quality issues are to be expected becoming more important. In this paper, we adopt software refactoring techniques to reduce the complexity of structure on source code level. It makes software program more effective to understand and modify, without any change of outward behavior. The existing AIS broadcast server program is used as an example for our trial, and calculating coupling and cohesion metric are introduced to analyze the refactoring effect, taking account of the maintainability of IEC/ISO9126 software quality standards.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2451-2461
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• 2014

Mobile application is software executing on smart devices regardless of the time and place. Many individuals and companies have provided a lot of mobile applications services. However, there is not certain standard in terms of application's quality evaluation because study is deficient compared with increase amount of development of mobile application. Moreover, mobile application basically has many special characteristics. For these reasons mobile application is required special standard of quality different from general software. To satisfy these needs, I design and propose mobile application evaluation model. Evaluation model is mapped by characteristics of mobile application based on ISO/IEC 25000's quality characteristics and propose each quality characteristics and metrics. For verification, scenario-based studies were applied to quality model and carried out.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1850-1859
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• 2009

The quality evaluation of software reliability for digital rights management rating will lead and as the technique it will be able to induce the quality increase of digital copyright management software the strategic engineering development which accommodates an international standard there is a possibility which an objectivity and an application degree it will raise. In order to evaluate the reliability quality of digital copyright management software from the research which it sees it proposed the tentative metric, it measured the result according to the standard which is appropriate it accomplished it presented it presented a quality and a research in about the method which it decides and an evaluation instance and a evaluation method clearly. The research which it sees it leads and it induces that there is a possibility of being sufficient it sees the reliability quality increase of digital copyright management software and the demand which is quantitative/qualitative in about digital copyright management software.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.199-206
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• 2023

The current software becomes the huge size of source codes. Therefore it is increasing the importance and necessity of static analysis for high-quality product. With static analysis of the code, it needs to identify the defect and complexity of the code. Through visualizing these problems, we make it guild for developers and stakeholders to understand these problems in the source codes. Our previous visualization research focused only on the process of storing information of the results of static analysis into the Database tables, querying the calculations for quality indicators (CK Metrics, Coupling, Number of function calls, Bad-smell), and then finally visualizing the extracted information. This approach has some limitations in that it takes a lot of time and space to analyze a code using information extracted from it through static analysis. That is since the tables are not normalized, it may occur to spend space and time when the tables(classes, functions, attributes, Etc.) are joined to extract information inside the code. To solve these problems, we propose a regularized design of the database tables, an extraction mechanism for quality metric indicators inside the code, and then a visualization with the extracted quality indicators on the code. Through this mechanism, we expect that the code visualization process will be optimized and that developers will be able to guide the modules that need refactoring. In the future, we will conduct learning of some parts of this process.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.780-787
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• 2005

Many researches and validations for the complexity metrics of the object-oriented systems have been studied. Most of them are aimed for the measurement of the partial aspects of the systems, for example, the coupling between objects, the complexity of inheritance structures, the cohesion of methods, and so on. But the software practitioners want to measure the complexity of overall system, not partial. We studied the complexity of the overall structures of object-oriented systems by analyzing the class diagram of UML. The class diagram is composed of classes and their relations. There are three kinds of relations, association, generalization, and aggregation, which are making the structure of object-oriented systems to be difficult to understand. We proposed a heuristic metric to measure the complexity of object-oriented systems by putting together the three kinds of the relations. Tn analyze the complexity of the structure of a object-oriented system for the maintainability of the system, we measured the degree of understandability of it, the reverse engineering time to draw a class diagram from the source codes, and the number of errors in the diagram. The results of this experiment shows that our proposed metric has a considerable relationship with the complexity of object-oriented systems. The metric will be helpful to the software developers for their designing tasks by evaluating the complexity of the structures of object-oriented systems and redesigning tasks , of them for the future maintainability.