• Korea Trade Review
• /
• v.48 no.3
• /
• pp.243-262
• /
• 2023

This study provides a systematic review of smart trade contracts, examining the research trends and theoretical background of utilizing smart contracts and blockchain technology for the digitalization and automation of trade contracts. Smart trade contracts are a concept that applies the automated contract system based on blockchain to trade-related transactions. The study analyzes the technical and legal challenges and proposes solutions. The technical aspect covers the development of smart contract platforms, scalability and performance improvements of blockchain networks, and security and privacy concerns. The legal aspect addresses the legal enforceability of smart contracts, automatic execution of contract conditions, and the responsibilities and obligations of contract parties. Smart trade contracts have been found to have applications in various industries such as international trade, supply chain management, finance, insurance, and energy, contributing to the ease of trade finance, efficiency of supply chains, and business model innovation. However, challenges remain in terms of legal regulations, interaction with existing legal frameworks, and technological aspects. Further research is needed, including empirical studies, business model innovation, resolution of legal issues, security and privacy considerations, standardization and collaboration, and user experience studies to address these challenges and explore additional aspects of smart trade contracts.

• Journal of Sensor Science and Technology
• /
• v.32 no.5
• /
• pp.320-327
• /
• 2023

In this study, an FPGA-based sealer inspection system was developed to inspect the sealer applied to install vehicle glass on a car body. The sealer is a liquid or paste-like material that promotes adhesion such as sealing and waterproofing for mounting and assembling vehicle parts to a car body. The system installed in the existing vehicle design parts line does not detect the sealer in the glass rotation section and takes a long time to process. This study developed a line laser camera sensor and an FPGA vision signal processing module to solve this problem. The line laser camera sensor was developed such that the resolution and speed of the camera for data acquisition could be modified according to the irradiation angle of the laser. Furthermore, it was developed considering the mountability of the entire system to prevent interference with the sealer ejection machine. In addition, a vision signal processing module was developed using the Zynq-7020 FPGA chip to improve the processing speed of the algorithm that converted the profile to the sealer shape image acquired from a 2D camera and calculated the width and height of the sealer using the converted profile. The performance of the developed sealer application inspection system was verified by establishing an experimental environment identical to that of an actual automobile production line. The experimental results confirmed the performance of the sealer application inspection at a level that satisfied the requirements of automotive field standards.

• 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.

• Journal of Drive and Control
• /
• v.20 no.4
• /
• pp.27-34
• /
• 2023

Weeding in orchards is closely associated with productivity and quality. The customary weeding process is both labor-intensive and time-consuming. To solve the problems, there is need for automation of agricultural robots and machines in the agricultural field. On the other hand, orchards have complicated working areas due to narrow spaces between trees and amorphous terrain. Therefore, it is necessary to develop customized robot technology for unmanned weeding work within the department. This study developed a path generation and path control method for unmanned weeding according to the orchard environment. For this, the width of the weeding span, the number of operations, and the width of the weeding robot were used as input parameters for the orchard environment parameters. To generate a weeding path, a weeding robot was operated remotely to obtain GNSS-based location data along the superheated center line, and a driving performance test was performed based on the generated path. From the results of orchard field tests, the RMSE in weeding period sections was measured at 0.029 m, with a maximum error of 0.15 m. In the steering period within row and steering to the next row sections, the RMSE was 0.124 m, and 0.047 m, respectively.

• Smart Media Journal
• /
• v.12 no.11
• /
• pp.67-76
• /
• 2023

We propose a visualization method to respond to civil complaints through an analysis of the impact of blasting. In order to analyze the impact of blasting on tunnel excavation, we propose a simulation visualization method considering the mutual influence of the construction infrastructure by linking measurement data and 3D BIM model. First, the level of BIM modeling required for simulation was defined. In addition, vibration measurement data were collected for the GTX-A construction site, terrain and structure BIM were created, and a method for visualizing measurement data using blast vibration estimation was developed. Next, a spherical blasting influence source library was developed for visualization of the blasting influence source, and a specification table that could be linked with Revit Dynamo automation logic was constructed. Using this result, a method for easily visualizing the impact analysis of blasting vibration in 3D was proposed.

• Journal of Drive and Control
• /
• v.21 no.2
• /
• pp.53-64
• /
• 2024

Global population growth has resulted in an increased demand for food production. Simultaneously, aging rural communities have led to a decrease in the workforce, thereby increasing the demand for automation in agriculture. Drones are particularly useful for unmanned pest control fields. However, the current method of uniform spraying leads to environmental damage due to overuse of pesticides and drift by wind. To address this issue, it is necessary to enhance spraying performance through precise performance evaluation. Therefore, as a foundational study aimed at optimizing drone-based pest control technologies, this research evaluated water-sensitive paper (WSP) via density map estimation using convolutional neural networks (CNN) with a encoder-decoder structure. To achieve more accurate estimation, this study implemented multi-task learning, incorporating an additional classifier for image segmentation alongside the density map estimation classifier. The proposed model in this study resulted in a R-squared (R²) of 0.976 for coverage area in the evaluation data set, demonstrating satisfactory performance in evaluating WSP at various density levels. Further research is needed to improve the accuracy of spray result estimations and develop a real-time assessment technology in the field.

• Smart Media Journal
• /
• v.13 no.1
• /
• pp.18-23
• /
• 2024

Power efficiency management in smart farms is important due to its link to climate change. As climate change negatively impacts agriculture, future agriculture is expected to utilize smart farms to minimize climate impacts, but smart farms' power consumption may exacerbate the climate crisis due to the current electricity production system. Therefore, it is essential to efficiently manage and optimize the power usage of smart farms. In this study, we propose a system that monitors the power usage of smart farm equipment in real time and predicts the power usage one hour later using GRU. CT sensors are installed to collect power usage data, which are analyzed to detect and prevent abnormal patterns, and combined with IoT technology to efficiently manage and monitor the overall power usage. This helps to optimize power usage, improve energy efficiency, and reduce carbon emissions. The system is expected to improve not only the energy management of smart farms, but also the overall efficiency of energy use.

• The Journal of the Convergence on Culture Technology
• /
• v.4 no.2
• /
• pp.197-204
• /
• 2018

One of the hottest issues in our 21st century is AI. Just as the automation of manual labor has been achieved through the Industrial Revolution in the agricultural society, the intelligence information society has come through the SW Revolution in the information society. With the advent of Google 'Alpha Go', the computer has learned and predicted its own machine learning, and now the time has come for the computer to surpass the human, even to the world of Baduk, in other words, the computer. Machine learning ML (machine learning) is a field of artificial intelligence. Machine learning ML (machine learning) is a field of artificial intelligence, which means that AI technology is developed to allow the computer to learn by itself. The time has come when computers are beyond human beings. Many companies use machine learning, for example, to keep learning images on Facebook, and then telling them who they are. We also used a neural network to build an efficient energy usage model for Google's data center optimization. As another example, Microsoft's real-time interpretation model is a more sophisticated translation model as the language-related input data increases through translation learning. As machine learning has been increasingly used in many fields, we have to jump into the AI industry to move forward in our 21st century society.

• Journal of the Korean Society for Railway
• /
• v.19 no.6
• /
• pp.736-743
• /
• 2016

In accordance with the trend of higher speed and automation, the Train Control System is building on the technology of control methods using radio in the technology of exchanging information by wire, toward a wireless communication method that will be applied using LTE-R radio communication technology with $4^{th}$ generation LTE mobile communication a $2^{nd}$ generation GSM-R. Therefore, a standard specification suitable for the Korea Radio based Train Control System-2(below KRTCS-2) for the 350km/h class using wireless communication is created; a prototype based on the standard specification is installed on a high-speed train and is installed on a test section(Ik san-Jeong eup) on the Honam high speed line to ensure the reliability and safety of the standard specifications, which are verified through various performance tests. In the future, the standard specification that has been established as a national railway standard, and the standard specifications will be commercialized by applying the train control system to conventional and High speed railway lines.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.19 no.4
• /
• pp.93-104
• /
• 2017

This study is a basic study to develop shoe last design technology to enhance and revitalize the competitiveness of the handmade shoes. In-depth interviews were conducted with four manufacturers in Seongsu-dong to identify the production status and design technology of shoe lasts. The result of the research is as follows. Firstly, shoe lasts for adults are produced at intervals of 5mm between 245mm-285mm for men's shoes, and between 220-260mm for women's shoes. The production rate of women's shoes was high in the order of general type, boot type, and sandal type while men's shoes mainly produce general type. Secondly, the master last size and ball girth rating for men's and women's shoes were analyzed to EE-EEE grade at 260mm and D grade at 235mm. The length of the master last for men's shoes is 276-290mm, the heel width is 60-65mm, the ball width is 88-90mm, the ball girth is 250mm, and the waist girth is 248mm. The length of the master shoe last for women's shoes is 236-245 mm, the heel width is 50-55mm, the ball width is 78-80mm, the ball girth is 211~213mm, and the waist girth is 213~215mm. Thirdly, the last grading deviation is 5mm in length, the heel width is 0.5mm, the ball girth is 3.5mm, and the ball with is 1.2mm. The ball girth dimensions of Oxford type, slip-on type, and sneakers type are made at 250mm, 248mm, and 245mm for men's shoes. For women's shoes, the ball girth dimensions of pump type, loafer & boot type, and sandal type are made at 211~213mm, 214~215mm, and 211mm. Fourthly, t+he construction of the automation system is insufficient and almost completely depends on manual production.