• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.71-73
• /
• 2019

How much and where vehicles exist is an essential element in the implementation of a GeoAI-based urban environment that reflects traffic information. In this paper, we trained vehicle data using Mask R-CNN that deep learning model useful for object detection and extraction, and verified vehicle detection in actual aerial images taken with drones.

• Tunnel and Underground Space
• /
• v.33 no.4
• /
• pp.209-227
• /
• 2023

The government continues to announce measures to revitalize smart construction technology based on BIM for productivity innovation in the construction industry. In the design phase, the goal is design automation and optimization by converging BIM Data and other advanced technologies. Accordingly, in the basic design of the Namhae Seomyeon-Yeosu Sindeok National Road Construction Project, a domestic undersea tunnel project, BIM-based design was carried out by developing tunnel design automation technology using 3D spatial information according to the tunnel design process. In order to derive the optimal alignment, more than 10,000 alignment cases were generated in 36hr using the generative design technique and a quantitative evaluation of the objective functions defined by the designer was performed. AI-based ground classification and 3D Geo Model were established to evaluate the economic feasibility and stability of the optimal alignment. AI-based ground classification has improved its precision by performing about 30 types of ground classification per borehole, and in the case of the 3D Geo Model, its utilization can be expected in that it can accumulate ground data added during construction. In the case of 3D blasting design, the optimal charge weight was derived in 5 minutes by reviewing all security objects on the project range on Dynamo, and the design result was visualized in 3D space for intuitive and convenient construction management so that it could be used directly during construction.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.42 no.8
• /
• pp.674-682
• /
• 2014

Radio Frequency Test Set (RFTS) is essential to verify Telemetry, Command & Ranging (TC&R) RF subsystem of both Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) satellite during Assembly Integration & Test (AI&T). The existing RFTS was specialized for each project and needed to be modified for each new satellite. The new design enables RFTS to be used in various projects. The hardware and software was designed considering this and therefore it could be directly used in other projects within a similar test period without modification or inconvenience. It will be also easily controlled, modified, and managed through the extension in modularization according to each function and the use of COTS (commercial on-the-self) and this will improve system reliability. A more reliable RF test measurement is also provided in this new RFTS by using an accurate reference clock signal.

• Journal of Korean Library and Information Science Society
• /
• v.54 no.1
• /
• pp.45-68
• /
• 2023

This study aims to investigate the awareness and experiences of domestic researchers regarding data publishing, which has been recognized as a new channel of data sharing as scholarly communication evolves in the open science environment. A survey is conducted among researchers from five government-funded research institutes in the field of science and technology and members of the GeoAI Data Society to confirm the awareness of data publishing. As a result of the study, domestic researchers recognized providing explanations for data, stable access to data, citation, and quality assurance through peer review as the advantages of data journals. On the contrary, a low level of recognition for data paper as one of the research outputs was presented. With regard to the properties of data publication, the respondents answered that the data description, metadata description, and permanent identifiers are highly related, however, their recognition of the relation between the properties of data publication and the data submission to a repository and data peer review was relatively low. Finally, to expand the data publication, the need for the development of an editorial system that supports data paper peer review and cross-linking to a data repository as well as the development of a repository that supports data citation was identified. This study on the domestic researchers' experience and awareness of data publishing can provide insights for the implementation of data publishing services and infrastructure in the future.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_3
• /
• pp.1771-1777
• /
• 2023

With the advancements of deep learning, many semantic segmentation-based methods for land cover classification have been proposed. However, existing deep learning-based models only use image information and cannot guarantee spatiotemporal consistency. In this study, we propose a land cover classification model using geographical coordinates. First, the coordinate features are extracted through the Coordinate Hash Encoder, which is an extension of the Multi-resolution Hash Encoder, an implicit neural representation technique, to the longitude-latitude coordinate system. Next, we propose an architecture that combines the extracted coordinate features with different levels of U-net decoder. Experimental results show that the proposed method improves the mean intersection over union by about 32% and improves the spatiotemporal consistency.

• Journal of the Korean Society of Industry Convergence
• /
• v.9 no.1
• /
• pp.61-66
• /
• 2006

In perspective of saving natural resource and energy, today's automobiles are in process of regenerating by smaller and lighter. In order to achieve the sufficiency on the consumption of the fuel, new mechanism and new assembly are required. Therefore the expectations on the new materials are very high. Especially, AI materials are widely used to reduce the weight. AI that is used in automobiles is mostly casting material, and according to the innovation of technique is in rapid development. AI Die casting is an important field as today's trend of lightweight on automobiles. One of the parts in steering system, Valve Housing plays a role of reduce the operating effort of drivers. Unfortunately, the Valve Housing which is widely reliable to the most automobiles are not developed at this moment in our automobile industry. Therefore, they are produced by casting method which cost three times or even more expensive in production. If Valve Housing, which is a part of steering system is produced by Gravity Casting, the space that manufacturing equipment will be increased, and more time and workers would be brought into service. For such reason, Die Casting would replace Gravity Casting in order to minimize cost of time, manpower, and working space.

• Economic and Environmental Geology
• /
• v.53 no.5
• /
• pp.609-617
• /
• 2020

After introducing the industry 4.0 policy, Korean government announced 'Digital New Deal' and 'Green New Deal' as 'Korean New Deal' in 2020. We analyzed Korea Institute of Geoscience and Mineral Resources (KIGAM)'s research projects related to that policy and conducted markets analysis focused on Digital Twin and environmental monitoring technologies. Regarding 'Data Dam' policy, we suggested the digital geo-contents with Augmented Reality (AR) & Virtual Reality (VR) and the public geo-data collection & sharing system. It is necessary to expand and support the smart mining and digital oil fields research for '5th generation mobile communication (5G) and artificial intelligence (AI) convergence into all industries' policy. Korean government is suggesting downtown 3D maps for 'Digital Twin' policy. KIGAM can provide 3D geological maps and Internet of Things (IoT) systems for social overhead capital (SOC) management. 'Green New Deal' proposed developing technologies for green industries including resource circulation, Carbon Capture Utilization and Storage (CCUS), and electric & hydrogen vehicles. KIGAM has carried out related research projects and currently conducts research on domestic energy storage minerals. Oil and gas industries are presented as representative applications of digital twin. Many progress is made in mining automation and digital mapping and Digital Twin Earth (DTE) is a emerging research subject. The emerging research subjects are deeply related to data analysis, simulation, AI, and the IoT, therefore KIGAM should collaborate with sensors and computing software & system companies.

• Korean Journal of Remote Sensing
• /
• v.14 no.4
• /
• pp.376-391
• /
• 1998

Images from satellites will have 1 to 3 meter ground resolution and will be very useful for analyzing current status of earth surface. An image processing system named GeoWatch with more intelligent image processing algorithms has been designed and implemented to support the detailed analysis of the land surface using high-resolution satellite imagery. The GeoWatch is a valuable tool for satellite image processing such as digitizing, geometric correction using ground control points, interactive enhancement, various transforms, arithmetic operations, calculating vegetation indices. It can be used for investigating various facts such as the change detection, land cover classification, capacity estimation of the industrial complex, urban information extraction, etc. using more intelligent analysis method with a variety of visual techniques. The strong points of this system are flexible algorithm-save-method for efficient handling of large size images (e.g. full scenes), automatic menu generation and powerful visual programming environment. Most of the existing image processing systems use general graphic user interfaces. In this paper we adopted visual program language for remotely sensed image processing for its powerful programmability and ease of use. This system is an integrated raster/vector analysis system and equipped with many useful functions such as vector overlay, flight simulation, 3D display, and object modeling techniques, etc. In addition to the modules for image and digital signal processing, the system provides many other utilities such as a toolbox and an interactive image editor. This paper also presents several cases of image analysis methods with AI (Artificial Intelligent) technique and design concept for visual programming environment.

• Geomechanics and Engineering
• /
• v.34 no.5
• /
• pp.507-527
• /
• 2023

Accurately estimation of the geo-mechanical parameters in Artificial Ground Freezing (AGF) is a most important scientific topic in soil improvement and geotechnical engineering. In order for this, one way is using classical and conventional constitutive models based on different theories like critical state theory, Hooke's law, and so on, which are time-consuming, costly, and troublous. The others are the application of artificial intelligence (AI) techniques to predict considered parameters and behaviors accurately. This study presents a comprehensive data-mining-based model for predicting the Young's Modulus of frozen sand under the triaxial test. For this aim, several single and hybrid models were considered including additive regression, bagging, M5-Rules, M5P, random forests (RF), support vector regression (SVR), locally weighted linear (LWL), gaussian process regression (GPR), and multi-layered perceptron neural network (MLP). In the present study, cell pressure, strain rate, temperature, time, and strain were considered as the input variables, where the Young's Modulus was recognized as target. The results showed that all selected single and hybrid predicting models have acceptable agreement with measured experimental results. Especially, hybrid Additive Regression-Gaussian Process Regression and Bagging-Gaussian Process Regression have the best accuracy based on Model performance assessment criteria.

• Tunnel and Underground Space
• /
• v.14 no.6 s.53
• /
• pp.399-410
• /
• 2004

The utilization of AS(Artificial Intelligence) and Database could be considered as an useful access for the application of underground information from the point of a geotechnical methodology. Its detailed usage has been recently studied in many fields of geo-sciences. In this paper, the target of usage is on controlling the injection of grout which more scientific access is needed in the grouting that has been used a major method in many engineering application. As the proposals for this problem it is suggested the methodology consisting of a fuzzy-neural hybrid system and a database. The database was firstly constructed for parameters dynamically varied according to the conditions of rock mass during the injection of grout. And then the conceptional model for the fuzzy-neural hybrid system was investigated fer optimally finding the controlling range of the grout valve. The investigated model applied to four cases, and it is found that the controlling range of the grout valve was reasonably deduced corresponding to the mechanical phenomena occurred by the injection of grout. Consequently, the algorithm organizing the fuzzy-neural hybrid system and the database as a system can be considered as a tool for controlling the injection condition of grout.