• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2831-2845
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• 2022

Compared to the significant approach of project-based learning research, a data-driven design project-based learning has not reached a meaningful consensus regarding the most valid and reliable method for assessing design creativity. This article proposes an advanced information data-interactive learning system for creative design using a service design process that combines a design thinking. We propose a service framework to improve the convergence design process between students and advanced information data analysis, allowing students to participate actively in the data visualization and research using patent data. Solving a design problem by discovery and interpretation process, the Advanced information-interactive learning framework allows the students to verify the creative idea values or to ideate new factors and the associated various feasible solutions. The student can perform the patent data according to a business intelligence platform. Most of the new ideas for solving design projects are evaluated through complete patent data analysis and visualization in the beginning of the service design process. In this article, we propose to adapt advanced information data to educate the service design process, allowing the students to evaluate their own idea and define the problems iteratively until satisfaction. Quantitative evaluation results have shown that the advanced information data-driven learning system approach can improve the design project - based learning results in terms of design creativity. Our findings can contribute to data-driven project-based learning for advanced information data that play a crucial role in convergence design in related standards and other smart educational fields that are linked.

• Journal of Life Science
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• v.31 no.4
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• pp.410-417
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• 2021

Next-generation sequencing (NGS) is a high-throughput technique for sequencing large numbers of DNA fragments that are prepared from a genome. This sequencing technique has been used to elucidate whole genome sequences of living organisms and to analyze complementary DNA (cDNA) or chromatin immunoprecipitated DNA (ChIPed DNA) at the genome level. After NGS, the use of proper tools is important for processing and analyzing data with reasonable parameters. However, handling large-scale sequencing data and programing for data analysis can be difficult. The Galaxy platform, a public web service system, provides many different tools for NGS data analysis, and it allows researchers to analyze their data on a web browser with no deep knowledge about bioinformatics and/or programing. In this study, we explain the procedure for preparing chromatin immunoprecipitation-sequencing (ChIP-seq) libraries and steps for analyzing ChIP-seq data using the Galaxy platform. The data analysis steps include the NGS data upload to Galaxy, quality check of the NGS data, premapping processes, read mapping, the post-mapping process, peak-calling and visualization by window view, heatmaps, average profile, and correlation analysis. Analysis of our histone H3K4me1 ChIP-seq data in K562 cells shows that it correlates with public data. Thus, NGS data analysis using the Galaxy platform can provide an easy approach to bioinformatics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.193-201
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• 2021

The welding has a high proportion of the production and drying of ships or offshore plants. Non-destructive testing is carried out to verify the quality of welds in Korea, radiography test (RT) is mainly used. Currently, most shipyards adopt analog-type techniques to print the films through the shoot of welding parts. Therefore, the time required from radiography test to pass or fail judgment is long and complex, and is being manually carried out by qualified inspectors. To improve this problem, this paper covers a platform for scanning and digitalizing RT films occurring in shipyards with high resolution, accumulating them in management servers, and applying artificial intelligence (AI) technology to detect welding defects. To do this, we describe the process of designing and developing RT film scanning equipment, welding inspection information integrated management platform, fault reading algorithms, visualization software, and testing and verification of each developed element in conjunction.

• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.19-34
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• 2015

One of the main causes of a limited use of nondestructive evaluation (NDE) technologies in bridge deck assessment is the speed of data collection and analysis. The paper describes development and implementation of the RABIT (Robotics Assisted Bridge Inspection Tool) for data collection using multiple NDE technologies. The system is designed to characterize three most common deterioration types in concrete bridge decks: rebar corrosion, delamination, and concrete degradation. It implements four NDE technologies: electrical resistivity (ER), impact echo (IE), ground-penetrating radar (GPR), and ultrasonic surface waves (USW) method. The technologies are used in a complementary way to enhance the interpretation. In addition, the system utilizes advanced vision to complement traditional visual inspection. Finally, the RABIT collects data at a significantly higher speed than it is done using traditional NDE equipment. The robotic system is complemented by an advanced data interpretation. The associated platform for the enhanced interpretation of condition assessment in concrete bridge decks utilizes data integration, fusion, and deterioration and defect visualization. This paper concentrates on the validation and field implementation of two NDE technologies. The first one is IE used in the delamination detection and characterization, while the second one is the USW method used in the assessment of concrete quality. The validation of performance of the two methods was conducted on a 9 m long and 3.6 m wide fabricated bridge structure with numerous artificial defects embedded in the deck.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.3
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• pp.369-375
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• 2010

Since multi-view images can be utilized for 3D visualization and surveying as well, a system calibration is an essential procedure. The cameras in the system are mounted to the holder and their locations and attitudes are relatively fixed. Therefore, the locations and the attitudes of the perspective centers of the four oblique looking cameras can be calculated using the location and attitude of the nadir looking camera and the boresight values between the cameras. In this regard, this research is focusing on the analysis of the relative location and attitude between the nadir and oblique looking cameras based on the results of the exterior orientation parameters after the aerial triangulation of the real multiview images. We acquired high standard deviations of the relative locations between the nadir and oblique cameras. Standard deviations of the relative attitudes between the cameras were low when only the exterior orientations of the oblique looking cameras were allowed to be adjusted. Moreover, low standard deviations of the relative attitudes came when we considered not all the exterior orientations of the cameras but the attitudes of them only.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.6
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• pp.60-71
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• 2019

As IoT systems such as smart farms and smart cities become popular, a large amount of data collected from many sensor nodes is sent to a server in the Internet, which causes network traffic explosion, delay in delivery, and increase of server's workload. To solve these problems, the concept of fog computing has been proposed to store data between IoT systems and servers. In this study, we implemented a software platform of the fog node and applied it to the prototype smart farm system in order to check whether the problems listed above can be solved when using the fog node. When the fog node is used, the time taken to control an IoT device is lower than the response time of the existing IoT device-server case. We confirmed that it can also solve the problem of the Internet traffic explosion and the workload increase in the server. We also showed that the intelligent control of IoT system is feasible by having the data visualization in the server and real time remote control, emergency notification in the fog node as well as data storage which is the basic capability of the fog node.

• Convergence Security Journal
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• v.18 no.1
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• pp.33-42
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• 2018

CFD analysis is an analytical technique that applies a computer to the design and development of products across the entire industry for heat or fluid flow. This technology is used to shorten the development period and reduce costs through computerized simulation. However, the software used for CFD analysis is now required to use expensive foreign software. The Opensource CFD analysis software used in the proposed system has reliability of commercial CFD analysis software and has various user groups. However, for users who have expert knowledge, Opensource CFD software which supports only text interface environment, We have developed an environment that enables the construction of a CFD analysis environment for beginners as well as professionals. In addition, the proposed system supports the pre-processing (design and meshing) environment for CFD analysis and the environment for post-processing (result analysis & visualization), enabling the integrated CFD analysis process in one platform.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.571-576
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• 2021

This study was carried out to overcome the problems of the existing fitness business and to build a fitness system that can meet the increased demand in the Corona situation. As a platform technology for non-face-to-face fitness edutainment service, it is a next-generation fitness exercise device that can use various body parts and synchronize network-type information. By synchronizing the exercise information of the fitness equipment, it was composed of learning contents through MR-based avatars. A quantified result was derived from examining the applicability of the customized evaluation system through momentum analysis with A.I analysis applying the LSTM-based algorithm according to the cumulative exercise effect of the user. It is a motion capture and 3D visualization fitness program for the application of systematic exercise techniques through academic experts, and it is judged that it will contribute to the improvement of the user's fitness knowledge and exercise ability.

• Journal of KIBIM
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• v.12 no.4
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• pp.61-69
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• 2022

Earthmoving operations account for approximately 25% of construction cost, generally executed prior to the construction of buildings and structures with heavy equipment. For the successful completion of earthwork projects, it is crucial to constantly monitor earthwork equipment (e.g., trucks), estimate productivity, and optimize the construction process and equipment on a construction site. Traditional methods however require time-consuming and painstaking tasks for the manual observations of the ongoing field operations. This study proposed the use of a GPS sensor embedded in a smartphone for the tracking and visualization of equipment locations, which are in turn used for the estimation and simulation of cycle times and production rates of ongoing earthwork. This approach is implemented into a digital platform enabling real-time data collection and simulation, particularly in a 2D (e.g., maps) or 3D (e.g., point clouds) virtual environment where the spatial and temporal flows of trucks are visualized. In the case study, the digital platform is applied for an earthmoving operation at the site development work of commercial factories. The results demonstrate that the production rates of various equipment usage scenarios (e.g., the different numbers of trucks) can be estimated through simulation, and then, the optimal number of tucks for the equipment fleet can be determined, thus supporting the practical potential of real-time sensing and simulation for onsite equipment management.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.289-304
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• 2022

It is necessary to apply process algebra and logic in order to analyze and verify safety requirements for Smart IoT Systems due to distributivity and mobility of the systems over some predefined geo-temporal space. However the analysis and verification cannot be fully intuitive over the space due to the fact that the existing process algebra and logic are very limited to express the distributivity and the mobility. In order to overcome the limitations, the paper presents a new logic, namely for GTS-VL (Geo-Temporal Space-Visual Logic), visualization of the analysis and verification over the space. GTS-VL is the first order logic that deals with relations among the different types of blocks over the space, which is the graph that visualizes the system behaviors specified with the existing dTP-Calculus. A tool, called SAVE, was developed over the ADOxx Meta-Modeling Platform in order to demonstrate the feasibility of the approach, and the advantages and practicality of the approach was shown with the comparative analysis of PBC (Producer-Buffer-Consumer) example between the graphical analysis and verification method over the textual method with SAVE tool.