• The Journal of Society for e-Business Studies
• /
• v.15 no.2
• /
• pp.19-35
• /
• 2010

In response to an increased need, various methods for ontology modularization have been proposed. However, few studies have focused on evaluative methods for ontology modules. In this study, we devise novel metrics to measure ontology modularity. To evaluate the ontology modules, we introduce cohesion and coupling based on the theory of software metrics. A cohesion metric and two coupling metrics were used to measure cohesion and coupling for ontology modules. These metrics were also used to check consistency between the ontology modules and the original ontology. The new metrics support a more detailed relationship between classes in ontology modules. We validate the proposed metrics using the well known verification framework and perform the empirical experiments to complement previous investigations. This study offers ontology engineers valuable criteria with which to select and use ontology modules and modularization techniques.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.1
• /
• pp.197-206
• /
• 2015

Defect severity that is a measure of the impact caused by the defect plays an important role in software quality activities because not all software defects are equal. Earlier studies have concentrated on defining defect severity levels, but there have almost never been trials of measuring module severity. In this paper, first, we define a defect severity metric in the form of an exponential function using the characteristics that defect severity values increase much faster than severity levels. Then we define a new metrics set for software module severity using the number of defects in a module and their defect severity metric values. In order to show the applicability of the proposed metrics, we performed an analytical validation using Weyuker's properties and experimental validation using NASA open data sets. The results show that ms is very useful for measuring the module severity and msd can be used to compare different systems in terms of module severity.

• Journal of KIISE:Computing Practices and Letters
• /
• v.7 no.2
• /
• pp.151-164
• /
• 2001

Java, used as the most representative object-oriented language, isil becoming the popular language for Internet/Intranet based program development. Moreover, it is used for development language in a variety of areas such as component based development language. In the view of reuse and maintenance of developed program, quality evaluation of program is becoming a more important issue. So, metrics measurement for quality evaluation of program that is developed at present including existing Java application is necessary. However, it is necessary that whether existing object-oriented software metrics is suitable on Java program is to be validated So, in this paper, we build an automated metrics measurement system that needs to validate on object-oriented software metrics and wish to support metrics measurement that is to determine it. The purpose of this system is to support a precise quality evaluation tool. In this system, we apply the metrics classified by Briand. Briand classified the metrics by formalizing mathematically them to verify feasibility of existing object-oriented software metrics. Using the proposed system, we can make comparison and analysis of validation on existing object-oriented metrics by calculating quantitative information more rapidly from Java source program. If there is any problem in feasibility of the metrics, we can establish a suitable metrics on Java program by considering reiJ,1forcement of the existing metrics or proposing new metrics.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.3
• /
• pp.75-84
• /
• 2007

Due to the increasing complexity and shorter life cycle of web applications, web applications need to be restructured to improve flexibility and extensibility. These days approaches are being used where systems are understood and restructured through clustering techniques. In this paper, the coupling metrics are proposed for clustering web pages more effectively. To achieve this, web application models are defined, where the relationship between web pages and the numbers of parameters are included. Considering direct and indirect coupling strength based on these models, coupling metrics are defined. The more direct relations between two pages and the more parameters they have, the stronger direct coupling is. The higher indirect connectivity strength between two pages is, the more similar the patterns of relationships among other web pages are. We verify the suggested metrics according to the well known verification framework and provide a case study to show that our metrics complements some existing metrics.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2021.07a
• /
• pp.51-52
• /
• 2021

본 논문에서는 얼굴 검증(Face Verification) 문제를 해결하기 위한 방법론으로 깊은 삼중 항 네트워크 모델을 제안한다. 본 논문에서는 얼굴 검증을 거리기반 유사도 문제로 보고, 딥러닝 기반 메트릭 러닝으로 해결하고자 하였다. 딥 메트릭 러닝 중 하나인 삼중 항 네트워크를 깊게 쌓기 위해 ResNet50, ResNet101과 경량화 모델인 MobileNet v3를 적용하였으며, 위 모델을 사용함으로써 이미지의 특징 추출을 효과적으로 할 수 있었다. 본 연구에서 제시한 방법론은 추후 복잡한 모델이 필요한 영상 데이터 내 얼굴 식별 모델에 기초 연구로서의 의의가 있다.

• The KIPS Transactions:PartD
• /
• v.12D no.4 s.100
• /
• pp.609-616
• /
• 2005

The component-based development methodology becomes famous as the reuse technology to improve the high productivity of software development. It is necessary component metrics for component-based systems, because the designed components should be measurable to improve the quality of the software. Therefore this paper propose a coupling metric for component design which is reflected in characteristics of component. This paper suggest a case study and comparative analysis result about conventional metrics to verify the accuracy of our coupling metric. The Uoposed coupling metric measure the quality of components accurately and satisfies necessary conditions of coupling metric suggested by Briand and others.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.12
• /
• pp.151-158
• /
• 2021

Internet of Things (IoT) technology, which provides services by connecting various objects in the real world and objects in the virtual world based on the Internet, is emerging as a technology that enables a hyper-connected society in the era of the 4th industrial revolution. Since IoT technology is a convergence technology that encompasses devices, networks, platforms, and services, various studies are being conducted. Among these studies, studies on measures that can measure service quality provided by IoT software are still insufficient. IoT software has hardware parts of the Internet of Things, technologies based on them, features of embedded software, and network features. These features are used as elements defining IoT software quality measurement metrics. However, these features are considered in the metrics related to IoT software quality measurement so far. Therefore, this paper presents a metric for reusability measurement among various quality factors of IoT software in consideration of these factors. In particular, since IoT software is used through IoT devices, services in IoT software must be designed to be changed, replaced, or expanded, and metrics that can measure this are very necessary. In this paper, we propose three metrics: changeability, replaceability, and scalability that can measure and evaluate the reusability of IoT software services were presented, and the metrics presented through case studies were verified. It is expected that the service quality verification of IoT software will be carried out through the metrics presented in this paper, thereby contributing to the improvement of users' service satisfaction.

• Journal of Broadcast Engineering
• /
• v.20 no.2
• /
• pp.204-214
• /
• 2015

Depth map upsampling is an approach to increase the spatial resolution of depth maps obtained from a depth camera. Depth map quality is closely related to 3D perception of stereoscopic image, multi-view image and holography. In general, the performance of upsampled depth map is evaluated by PSNR (Peak Signal to Noise Ratio). On the other hand, time-consuming 3D subjective tests requiring human subjects are carried out for examining the 3D perception as well as visual fatigue for 3D contents. Therefore, if an objective metric is closely correlated with a subjective test, the latter can be replaced by the objective metric. For this, this paper proposes a best metric by investigating the relationship between diverse objective metrics and 3D subjective tests. Diverse reference and no-reference metrics are adopted to evaluate the performance of upsampled depth maps. The subjective test is performed based on DSCQS test. From the utilization and analysis of three kinds of correlations, we validated that SSIM and Edge-PSNR can replace the subjective test.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.19 no.5
• /
• pp.131-142
• /
• 2009

While users of information security products require high-quality products that are secure and have high performance, there are neither examples for evaluating the quality of information security products nor studies on the quality model and metrics for the quality evaluation. In this paper, information security products are categorized into three different types and the security and performance of various information security products are analyzed. Through this process and after consideration of information security products' security and performance, a new quality model that possesses 7 characteristics and 24 sub-characteristics has been defined. In addition, metrics consisting of 62 common and 45 extended metrics that can be used to evaluate the quality of information security products are introduced, and a proposition for a method of generating the quality evaluation metrics for specific information security products is included. The method of generating metrics proposed in this paper can be extended in order to be applied to a variety of information security products, and by generating and verifying the quality evaluation metrics for firewall, intrusion detection systems and fingerprint systems it is shown that it applicable on a variety of information security products.

• Smart Media Journal
• /
• v.12 no.2
• /
• pp.66-75
• /
• 2023

Recently, the number of cloud web applications is increasing owing to the accelerated migration of enterprises and public sector information systems to the cloud. Traditional network attacks on cloud web applications are characterized by Denial of Service (DoS) attacks, which consume network resources with a large number of packets. However, HTTP DoS attacks, which consume application resources, are also increasing recently; as such, developing security technologies to prevent them is necessary. In particular, since low-bandwidth HTTP DoS attacks do not consume network resources, they are difficult to identify using traditional security solutions that monitor network metrics. In this paper, we propose a new detection model for detecting HTTP DoS attacks on cloud web applications by collecting the application metrics of web servers and learning them using machine learning. We collected 18 types of application metrics from an Apache web server and used five machine learning and two deep learning models to train the collected data. Further, we confirmed the superiority of the application metrics-based machine learning model by collecting and training 6 additional network metrics and comparing their performance with the proposed models. Among HTTP DoS attacks, we injected the RUDY and HULK attacks, which are low- and high-bandwidth attacks, respectively. As a result of detecting these two attacks using the proposed model, we found out that the F1 scores of the application metrics-based machine learning model were about 0.3 and 0.1 higher than that of the network metrics-based model, respectively.