• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.32-42
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• 2023

There are serious problems worldwide, such as a pandemic due to an unprecedented infection caused by COVID-19. On previous approaches, they invented medical vaccines and preemptive testing tools for medical engineering. However, it is difficult to access poor medical systems and medical institutions due to disparities between countries and regions. In advanced nations, the damage was even greater due to high medical and examination costs because they did not go to the hospital. Therefore, from a software engineering-based perspective, we propose a learning model for determining coronavirus infection through symptom data-based software prediction models and tools. After a comparative analysis of various models (decision tree, Naive Bayes, KNN, multi-perceptron neural network), we decide to choose an appropriate decision tree model. Due to a lack of data, additional survey data and overseas symptom data are applied and built into the judgment model. To protect from thiswe also adapt human normalization approach with traditional Korean medicin approach. We expect to be possible to determine coronavirus, flu, allergy, and cold without medical examination and diagnosis tools through data collection and analysis by applying decision trees.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1462-1471
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• 2019

Real-time embedded systems have become pervasive in general industry. They also began to be applied in such domains as avionics, automotive, aerospace, healthcare, and industrial Internet. However, the system failure of such domains could result in catastrophic consequences. Runtime software testing is required in such domains that demands very high accuracy. Traditional runtime software testing based on handwork is very inefficient and time consuming. Hence, test automation methodologies in runtime is demanding. In this paper, we introduce a software testing system that translates a real-time software into a monitorable real-time software. The monitorable real-time software means the software provides the monitoring information in runtime. The monitoring target are time constraints of the input real-time software. We anticipate that our system lessens the burden of runtime software testing.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.213-220
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• 2001

This paper presents the interrelationship between software quality character and engineering attributes. The software quality characteristics and subcharacteristics are excerpted from IS0/IEC 9126 standards, and the engineering attributes are from Deutsch and Willis〔4〕. Based on the previous studies a subjective judgement, trisected interrelationship(strong, medium, weak) bet these two groups are derived. The results are summarized in a table, and can be used as a quick reference guide to the software quality engineering application such as quality evaluations for software products, selection of key engineering attributes for high-quality software production, and so forth.

• Journal of information and communication convergence engineering
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• v.4 no.1
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• pp.23-27
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• 2006

The discipline of software performance is very broad; it influences all aspects of the software development lifecycle, including architecture, design, deployment, integration, management, evolution and servicing. Thus, the complexity of software is an important aspect of development and maintenance activities. Much research has been dedicated to defining different software measures that capture what software complexity is. In most cases, the description of complexity is given to humans in forms of numbers. These quantitative measures reflect human-seen complexity with different levels of success. Software complexity growth has been recognized to be beyond human control. In this paper, we have focused our discussion on the increasing software complexity and the issue with the problems being faced in managing this complexity. This increasing complexity in turn affects the software productivity, which is declining with increase in its complexity.

• International Journal of Contents
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• v.13 no.1
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• pp.38-44
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• 2017

Increased use of software and complexity of software functions, as well as shortened software quality evaluation periods, have increased the importance and necessity for automation of software testing. Automating software testing by using machine learning not only minimizes errors in manual testing, but also allows a speedier evaluation. Research on machine learning in automated software testing has so far focused on solving special problems with algorithms, leading to difficulties for the software developers and testers, in applying machine learning to software testing automation. This paper, proposes a new machine learning framework for software testing automation through related studies. To maximize the performance of software testing, we analyzed and categorized the machine learning algorithms applicable to each software test phase, including the diverse data that can be used in the algorithms. We believe that our framework allows software developers or testers to choose a machine learning algorithm suitable for their purpose.

• Journal of the Korea Society of Computer and Information
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• v.17 no.8
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• pp.123-133
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• 2012

Recently, as IT convergence has seen rapid growth the role and scope of software has been extended. many software companies are trying to improve the software quality and project outcome using software process improvement approach to cope with increasing software demands and software quality. Although software process improvement is difficult task which requires a lot of cost and time, there is still insufficient objective evidence on business benefits by its deployment. The purpose of this study is to analyze the relationship between software process improvement and software project productivity. That is, we investigated whether there is difference in software development productivity depends on software engineering level using statistical methods. We found that the software development productivity is different across the software engineering levels and the higher software engineering level can lead to improved software development productivity.

• Journal of Software Engineering Society
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• v.26 no.1
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• pp.17-29
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• 2013

Software System Evolution is more planned and systematic maintenance process as well as a type of maintenance. The research of software evolution provides basis of decisions for maintenance value through cost-benefit analysis of legacy system and architecture-based software evolution enables engineers to reduce maintenance cost by automation of repetitive evolution tasks. This paper proposes a framework for software system evolution using architectural transformation pattern.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.65-72
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• 2018

In this paper, we have studied how to reuse common data link software by applying software product line engineering. Existing common data link software performed different stages of design, implementation, and testing without sharing the accumulated knowledge of different developers. In this situation, developers agreed that sharing the assets of each project and reusing the previously developed software would save human and time costs. Even with the initial difficulties, the common Data Link is a continually proposed project in the defense industry, so we decided to build a product line. The common data link software can be divided into two domains. Among them, the initial feature model for the GUI software was constructed, and the following procedure was studied. Through this, we propose a plan to build a product line for core assets and reuse them in newly developed projects.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.185-186
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• 2009

VOD 서비스는 초고속 인터넷을 이용하여 정보 서비스, 동영상 콘텐츠 및 방송 등을 실시간으로 제공하는 것이다. 본 연구에서 구현하는 VOD 시스템은 기존 인터넷망에 멀티캐스트 기술을 접목하여, 비트열변환 방식과 다수개 영상저장 방식을 비교한다. 이로부터 동영상을 각 가정의 PC에 고화질 주문형 비디오/영화, TV 등 다양한 고품질 서비스를 제공할 수 있을 것이다.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.168-174
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• 2023

In the current world, with the massive scale of SOC construction, it is difficult to diagnose and check all of a bridge's abnormal states with even the experts' eyes for maintenance. It is because we should spend huge costs and time on maintenance. Still, there are not many alternative ways to inspect bridges remotely regarding accuracy or reality. Therefore, we remark on the advantages and disadvantages of previous methods through practices in SOC maintenance. To inspect the abnormal state of the Bridge, we suggest inspecting bridges with an Augmented Reality (AR) mechanism to reduce cost, human resource consumption, and the risk of work. Through the proposed approach, we expect that it provides ways to solve massive construction problems with software-based technologies.