• International Journal of Knowledge Content Development & Technology
• /
• v.6 no.1
• /
• pp.69-84
• /
• 2016

The paper investigates open access (OA) self archiving policies of different Open Access Repositories (OARs) of COAPI (Coalition of Open Access Policy Institutions) founder members as reported in June 2011 (i.e. a total of 22 members against a total of 46 COPAI members as reported by Open Biomed (http://openbiomed.info/2011/08/coapi-cats/). The paper consulted three databases (OpenDOAR, ROAR and ROARMAP) in order to evaluate twenty-two (22) COAPI-members OARs self archiving policy documentations and highlights of some progress on issues so far. After analyzing policy documentations, key findings have been highlighted and common practices have been suggested in line with global recommendations and best practice guidelines at national and international levels for strengthening national research systems. The paper has implications for administrators, funding agencies, policy makers and professional librarians in devising institute specific self archiving policies for their own organization.

• Korean Journal of Remote Sensing
• /
• v.25 no.6
• /
• pp.559-569
• /
• 2009

During over decades, metadata on spatial data have been developed, and they have been widely applied at the national and international metadata standards such as file structure, format, and data model. However, in the web 2.0 paradigm toward user participation and openness, sources and contents of geospatial products are also diversified, not being limited to well-organized and structured data sets or databases. Especially, software products in both open source software and commercially packaged software are considered into important resources in the geospatial domain. But there are no reports or studies regarding software metadata from the side of software engineering or information technology, till now. The motivation of this study is based on practical needs to build search engine in the intelligent geospatial web. Brief review on current metadata standards is presented, and necessity for software metadata is discussed as well as related works. Basic elements, initially considered, of software metadata are presented. This work is the first attempt for software metadata, although it just covers geospatial software products. Further practical works to meet industrial demands need to actual applications of software metadata.

• Journal of the Korea Society of Computer and Information
• /
• v.23 no.4
• /
• pp.97-106
• /
• 2018

Software maintenance activities have always been important issues in many domains of the software industry. In order to help to resolve this issue, software modularization approaches have been studied to build adequate modules with high cohesion and low coupling; such modular structures can help the comprehension and maintenance of complex systems. In this paper, we propose a GUI-based automated approach for software modularization based on GUI structure analysis. GUI is a principal manner to allow users to access the overall functionalities of a software system; in particular, GUI is closely related to software functionalities, which makes it a promising tool to identify and understand the entire software system. We also implement a software tool to support our approach and evaluate it with a case study using an open source software.

• Journal of Information Processing Systems
• /
• v.18 no.6
• /
• pp.741-754
• /
• 2022

Openstack is widely used as a representative open-source infrastructure of the service (IaaS) platform. The Openstack Identity Service is a centralized approach component based on the token including the Memcached for cache, which is the in-memory key-value store. Token validation requests are concentrated on the centralized server as the number of differently encrypted tokens increases. This paper proposes the practical Byzantine fault tolerance (PBFT) blockchain-based Openstack Identity Service, which can improve the performance efficiency and reduce security vulnerabilities through a PBFT blockchain framework-based decentralized approach. The experiment conducted by using the Apache JMeter demonstrated that latency was improved by more than 33.99% and 72.57% in the PBFT blockchain-based Openstack Identity Service, compared to the Openstack Identity Service, for 500 and 1,000 differently encrypted tokens, respectively.

• The Journal of Information Systems
• /
• v.29 no.2
• /
• pp.149-171
• /
• 2020

Purpose With the advent of the 4th Industrial Revolution, related technologies such as IoT, big data, and artificial intelligence technologies are developing through not only specific companies but also a number of unspecified developers called open collaboration. For this reason, it is important to understand the nature of the collaboration that leads to successful open collaboration. Design/methodology/approach We focused the relationship between the collaboration characteristics and collaboration performance of developers who participating in open source software development, which is a representative open collaboration. Specifically, we create the country-specific network and draw the individual developers characteristics from the network such as collaboration scope and collaboration intensity. We compare and analyze the characteristics of developers across countries and explore whether there are differences between indicators. We develop a Web crawler for GitHub, a representative OSSD development site, and collected data of developers who located at China, Japan, Korea, the United States, and Canada. Findings China showed the characteristics of cooperation suitable for the form of weak tie theory, and consistent results were not drawn from other countries. This study confirmed the necessity of exploratory research on collaboration characteristics by country considering that there are differences in open collaboration characteristics or software development environments by country.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.4
• /
• pp.89-96
• /
• 2021

The number of confirmed cases of coronavirus-19 is soaring around the world and has caused numerous deaths. Wearing a mask is very important to prevent infection. Incidents and accidents have occurred due to the recommendation to wear a mask in public places such as buses and subways, and it has emerged as a serious social problem. To solve this problem, this paper proposes an open source-based face mask wearing monitoring system. We used open source software, web-based artificial intelligence tool teachable machine and open source hardware Arduino. It judges whether the mask is worn, and performs commands such as guidance messages and alarms. The learning parameters of the teachable machine were learned with the optimal values of 50 learning times, 32 batch sizes, and 0.001 learning rate, resulting in an accuracy of 1 and a learning error of 0.003. We designed and implemented a mask wearing monitoring system that can perform commands such as guidance messages and alarms by determining whether to wear a mask using a web-based artificial intelligence tool teachable machine and Arduino to prove its validity.

• The Journal of Korean Society for School & Community Health Education
• /
• v.11 no.1
• /
• pp.67-78
• /
• 2010

Background & Objectives: Current trend is that funding agencies require investigators to share their data with others. However, there is limited guidance how to access and utilize the shared data. We sought to determine what common data sharing practices in U.S.A. are, what data-related to adolescent health are freely available, and how we deal with the large dataset adopting the complex study design. Methods: The study included only research data-related to adolescent health which was collected in USA and unlimitedly accessible through the internet. Only the raw data, not aggregated, was considered for the study. Major keywords for web search were "adolescent", "children", "health", and "school". Results: Current approaches for public health data sharing lacked of common standards and varied largely due to the data's complex nature, large size, local expertise and internal procedures. Some common data sharing practices are unlimited access, formal screened access, restricted access, and informal exclusive access. The Inter-University Consortium for Political and Social Research and the Center for Disease Control and Prevention were the best data depository. "Data on the net" was search engine for the website providing data freely available. Six datasets related to adolescent health freely available were identified. The importance and methods of incorporating complex research design into analysis was discussed. Conclusion: There have been various attempts to standardize process for open access and open data using the information technology concept. However, it may not be easy for researchers to adapt themselves to this high technology. Therefore, guidance provided by this study may help researchers enhance the accessibility to and the utilization of the open source data.

• Journal of Information Processing Systems
• /
• v.16 no.4
• /
• pp.915-934
• /
• 2020

Software refactoring is a process to restructure an existing software code while keeping its external behavior the same. Currently, various refactoring techniques are being used to develop more readable and less complex codes by improving the non-functional attributes of software. Refactoring can further improve code maintainability by applying various techniques to the source code, which in turn preserves the behavior of code. Refactoring facilitates bug removal and extends the capabilities of the program. In this paper, an exhaustive review is conducted regarding bad smells present in source code, applications of specific refactoring methods to remove that bad smell and its effect on software quality. A total of 68 studies belonging to 32 journals, 31 conferences, and 5 other sources that were published between the years 2001 and 2019 were shortlisted. The studies were analyzed based on of bad smells identified, refactoring techniques used, and their effects on software metrics. We found that "long method", "feature envy", and "data class" bad smells were identified or corrected in the majority of studies. "Feature envy" smell was detected in 36.66% of the total shortlisted studies. Extract class refactoring approach was used in 38.77% of the total studies, followed by the move method and extract method techniques that were used in 34.69% and 30.61% of the total studies, respectively. The effects of refactoring on complexity and coupling metrics of software were also analyzed in the majority of studies, i.e., 29 studies each. Interestingly, the majority of selected studies (41%) used large open source datasets written in Java language instead of proprietary software. At the end, this study provides future guidelines for conducting research in the field of code refactoring.

• Spatial Information Research
• /
• v.22 no.5
• /
• pp.87-98
• /
• 2014

Google Maps have changed the response time of Web-GIS using AJAX technologies. In addition, Google released the Open API named Google Maps API(Application Programming Interface) and it lead to the big paradigm on the Open API, where the SDK(Software Development Kit) and ASP(Application Service Provider) had ruled at the related map market. In short, the Open API has been paradigm-shifting for the web mapping. After this, government, many companies and open source foundations have guided Web-GIS market's growth through releasing the relevant Open APIs. So many comparative analysis on web-mapping API carried out by many researches. However there were no researches that can be applied to our current domestic environments. This paper investigates components of web-mapping API. Then we compare how many components supported and enumerate features for each of those APIs. Finally this paper presents direction of future development of Web Mapping API.

• Journal of the Korea Convergence Society
• /
• v.12 no.9
• /
• pp.11-19
• /
• 2021

A software system is required to change during its life cycle due to various requirements such as adding functionalities, fixing bugs, and adjusting to new computing environments. Such program code modification should be considered as carefully as a new system development becase unexpected software errors could be introduced. In addition, when reusing open source programs, we can expect higher quality software if code changes of the open source program are predicted in advance. This paper proposes a Convolutional Neural Network (CNN)-based deep learning model to predict source code changes. In this paper, the prediction of code changes is considered as a kind of a binary classification problem in deep learning and labeled datasets are used for supervised learning. Java projects and code change logs are collected from GitHub for training and testing datasets. Software metrics are computed from the collected Java source code and they are used as input data for the proposed model to detect code changes. The performance of the proposed model has been measured by using evaluation metrics such as precision, recall, F1-score, and accuracy. The experimental results show the proposed CNN model has achieved 95% in terms of F1-Score and outperformed the multilayer percept-based DNN model whose F1-Score is 92%.