• Journal of the Korea Society of Computer and Information
• /
• v.22 no.1
• /
• pp.63-69
• /
• 2017

In this paper, we propose a method to optimize the geometry and installation position of the mixer in the selective catalytic reduction (SCR) system by computational fluid dynamic(CFD). Using the commercial CFD software of CFD-ACE+, the flow dynamics of the flue gas was numerically analyzed for improving the injection uniformity of the reduction agent. Numerical analysis of the mixed gas heat flow into the upstream side of the primary SCR catalyst layer was performed when the denitrification facility was operated. The characteristics such as the flow rate, temperature, pressure loss and ammonia concentration of the mixed gas consisting of the flue gas and the ammonia reducing gas were examined at the upstream of the catalyst layer of SCR. The temperature difference on the surface of the catalyst layer is very small compared to the flow rate of the exhaust gas, and the temperature difference caused by the reducing gas hardly occurs because the flow rate of the reducing gas is very small. When the mixed gas is introduced into the SCR reactor, there is a slight tendency toward one wall. When the gas passes through the catalyst layer having a large pressure loss, the flow angle of the exhaust gas changes because the direction of the exhaust gas changes toward a smaller flow. Based on the uniformity of the flow rate of the mixed gas calculated at the SCR, it is judged that the position of the test port reflected in the design is proper.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.4
• /
• pp.27-36
• /
• 2022

In this paper, to improve the conditions of the fish processing site, we propose a method to predict the cutting point of fish according to the target weight using AI machine vision. The proposed method performs image-based preprocessing by first photographing the top and front views of the input fish. Then, RANSAC(RANdom SAmple Consensus) is used to extract the fish contour line, and then 3D external information of the fish is obtained using 3D modeling. Next, machine learning is performed on the extracted three-dimensional feature information and measured weight information to generate a neural network model. Subsequently, the fish is cut at the cutting point predicted by the proposed technique, and then the weight of the cut piece is measured. We compared the measured weight with the target weight and evaluated the performance using evaluation methods such as MAE(Mean Absolute Error) and MRE(Mean Relative Error). The obtained results indicate that an average error rate of less than 3% was achieved in comparison to the target weight. The proposed technique is expected to contribute greatly to the development of the fishery industry in the future by being linked to the automation system.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.1
• /
• pp.29-34
• /
• 2022

We propose a novel network architecture and build dataset for recognizing clickable objects on mobile device screens. The data was collected based on clickable objects on the mobile device screen that have numerous resolution, and a total of 24,937 annotation data were subdivided into seven categories: text, edit text, image, button, region, status bar, and navigation bar. We use the Deconvolution Single Shot Detector as a baseline, the backbone network with Squeeze-and-Excitation blocks, the Single Shot Detector layer structure to derive inference results and the Feature pyramid networks structure. Also we efficiently extract features by changing the input resolution of the existing 1:1 ratio of the network to a 1:2 ratio similar to the mobile device screen. As a result of experimenting with the dataset we have built, the mean average precision was improved by up to 101% compared to baseline.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.3
• /
• pp.13-26
• /
• 2009

In this raper, We propose the alternative solution, RTOS-based system to replace the PLC 4hat has used the automation system for industrial processes. RTOS-based system is constructed the PC and RTOS as hardware and software. It overcomes the limit of PLC and guarantees the stability and reliability. Also, PC has better performance and cheaper than PLC when operating and constructing the system. For many manufactures, these benefits alone are all the reason they need to switch from PLC-based system to RTOS-based system. To use the RTOS-based System, the PLC program needs the conversion to the RTOS task. And how to transform is the most important issue. So, we propose conversion method through the system model. The system model defines the operation of each module as the task after the system divided into module. Because the system divided into modules can control, the performance and the functionality of system improve, and the system can deal with a problem easily when repairing and changing.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.77-84
• /
• 2021

The purpose of this study is to propose AI maker coding education as a way to improve computational thinking(CT), which is an essential competence for problem-solving capability in modern society, and to analyze the effectiveness of this education on improving CT in elementary school students. For the research, 5 students from 4th graders and 5 students from 6th graders were recruited, and AI maker coding education was planned in 8 sessions to form classes from basic block coding and maker education to real-life problem solving. To analyze the effectiveness of AI maker coding education, pre- and post-CT examinations were performed. The test results confirmed that AI maker coding education had a significant effect on "abstraction", "algorithm", and "data processing" in the five CT components, and confirmed that there was no correlation in "problem resolution" and "automation". Overall, the average score of all students increased, and the deviation between students decreased, confirming that AI maker coding education was effective in improving CT.

• Journal of KIBIM
• /
• v.13 no.3
• /
• pp.21-29
• /
• 2023

ChatGPT, a chatbot based on GPT large language models, has gained immense popularity among the general public as well as domain professionals. To assess its proficiency in specialized fields, ChatGPT was tested on mainstream exams like the bar exam and medical licensing tests. This study evaluated ChatGPT's ability to answer questions related to Building Information Modeling (BIM) by testing it on Korea's BIM expertise exam, focusing primarily on multiple-choice problems. Both GPT-3.5 and GPT-4 were tested by prompting them to provide the correct answers to three years' worth of exams, totaling 150 questions. The results showed that both versions passed the test with average scores of 68 and 85, respectively. GPT-4 performed particularly well in categories related to 'BIM software' and 'Smart Construction technology'. However, it did not fare well in 'BIM applications'. Both versions were more proficient with short-answer choices than with sentence-length answers. Additionally, GPT-4 struggled with questions related to BIM policies and regulations specific to the Korean industry. Such limitations might be addressed by using tools like LangChain, which allow for feeding domain-specific documents to customize ChatGPT's responses. These advancements are anticipated to enhance ChatGPT's utility as a virtual assistant for BIM education and modeling automation.

• Advanced Industrial SCIence
• /
• v.3 no.1
• /
• pp.30-36
• /
• 2024

Recently, the Internet of Things (IoT), which has been applied to various industrial fields, is constantly evolving in the process of automation and digitization. However, in the network where IoT devices are built, research on IoT critical information-related data sharing, personal information protection, and data integrity among intermediate nodes is still being actively studied. In this study, we propose a blockchain-based IoT critical information management technique that is easy to implement without burdening the intermediate node in the network environment where IoT is built. The proposed technique allocates a random value of a random size to the IoT critical information arriving at the intermediate node and manages it to become a decentralized P2P blockchain. In addition, the proposed technique makes it easier to manage IoT critical data by creating licenses such as time limit and device limitation according to the weight condition of IoT critical information. Performance evaluation and proposed techniques have improved delay time and processing time by 7.6% and 10.1% on average compared to existing techniques.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.27 no.1
• /
• pp.751-760
• /
• 2009

This research aims to develop the strategy and method to enhance the reliability of image matching results and improve the efficiency of the matching process by utilizing LIDAR data in the main image matching processes. In this work, we present the methods to utilize LIDAR data in the selection of matching entities, the search for the matched entities and the evaluation of the matching results. The proposed method has been applied to medium-resolution digital aerial images and LIDAR data acquired at the same time. The results have been analyzed in comparison with an existing method using a virtual horizontal surface rather than LIDAR DEM. This analysis indicates that the proposed method can show significantly more improved performance than the existing method. The results of this study can contribute to the improvement of the currently available commercial image matching software and the enhancement of the DEM derived from LIDAR data and matching results.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.54 no.2
• /
• pp.147-156
• /
• 2012

가뭄강도와 지속기간을 고려하여 관개구역을 몇 개의 관개블록으로 나누어 순차적으로 제한하여 급수함으로써 관개용수를 절약하고 관개기간을 연장하여 가뭄을 극복하는 윤환관개모형 (RISS)을 제안한 바 있다. 이 RISS는 작물생육기별 관개저수지 저수율별 급수구역과 제한 급수율을 제시함으로써 가뭄기간에 저수지 운영자가 언제, 얼마나 제한하여 급수할 것인지 제시해주는 모형으로 전북 남원군 동화댐의 물 관리시스템 자동화 프로그램에 2004년 설치하여 운용되도록 하였다. 이 연구에서는 2004년부터 2009년까지 동화 댐 저수위 관측기록과 급수실적을 분석하여 RISS의 절수효과를 평가하고자 하였다. 그러나 실제로는 동화댐의 물 관리시스템 자동화 프로그램이 계획대로 운용되지 않고 있었다. 따라서 이 RISS의 절수효과와 효용성을 입증하여 계획대로 자동화시스템을 유용하게 활용하도록 하기 위해서 급수실적 및 저수위 관측기록과 RISS로 모의 발생한 저수위 결과를 비교 평가하였다. 모의발생 평가결과 가뭄이 극심했던 2007년에는 3.8백만 $m^3$을 절수하여 관개기간을 23일 연장하고 2009년에는 3.3백만 $m^3$을 절수하여 관개기간을 13일 연장하여 가뭄이 극심한 해에는 RISS 모형의 효용성이 크다는 것을 알 수 있었다.

• Journal of the Society of Naval Architects of Korea
• /
• v.41 no.6
• /
• pp.126-133
• /
• 2004

As the automation of ship production system proliferates, it is unavoidable to move the real machinery, facility, application software, and virtual environment from the heterogeneous data environment to the integrated one. However, it is a prevailing situation that each component operates under the different environment, due to the inability of interchanging the data in a structured manner between the components. The issue is obstacles to improvement of the application system. To facilitate seamless exchange of data among the manufacturing systems, STEP, PDML, and XML has been tried by other studies. This study has investigated how XML data can be applied to exchange the data among the ship production system components. XML data is applied to the forming shop in shipyard to overcome the present difficulties on sharing and exchanging of the information. An example of forming information is represented by XML to demonstrate the feasibility of the proposed approach. In addition, an application of XML information applicable to virtual factory and electronic work order sheet is included.