• The Journal of Bigdata
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• v.7 no.2
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• pp.31-41
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• 2022

Steel is one of the most fundamental components to mechanical industry. However, the quality of products are greatly impacted by the surface defects in the steel. Thus, researchers pay attention to the need for surface defects detector and the deep learning methods are the current trend of object detector. There are still limitations and rooms for improvements, for example, related works focus on developing the models but don't take into account real-time application with practical implication on industrial settings. In this paper, a real-time application of steel surface defects detection based on YOLOv4 is proposed. Firstly, as the aim of this work to deploying model on real-time application, we studied related works on this field, particularly focusing on one-stage detector and YOLO algorithm, which is one of the most famous algorithm for real-time object detectors. Secondly, using pre-trained Yolov4-Darknet platform models and transfer learning, we trained and test on the hot rolled steel defects open-source dataset NEU-DET. In our study, we applied our application with 4 types of typical defects of a steel surface, namely patches, pitted surface, inclusion and scratches. Thirdly, we evaluated YOLOv4 trained model real-time performance to deploying our system with accuracy of 87.1 % mAP@0.5 and over 60 fps with GPU processing.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.389-394
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• 2023

In recent years, use of machine automation is rising in the industry. Ships also obtain machine condition information from sensor as digital information. However, on ships, crew members regularly surveil the engine room to check the condition of equipment and their information through analog gauges. This is a time-consuming and tedious process and poses safety risks to the crew while on surveillance. To address this, engine room surveillance using an autonomous mobile robot is being actively explored as a solution because it can reduce time, costs, and the safety risks for crew. Analog gauge reading using an autonomous mobile robot requires digitization for the robot to recognize the gauge value. In this study, image processing techniques were applied to achieve this. Analog gauge images were subjected to image preprocessing to remove noise and highlight their features. The center point, indicator point, minimum value and maximum value of the analog gauge were detected through image processing. Through the straight line connecting these points, the angle from the minimum value to the maximum value and the angle from the minimum value to indicator point were obtained. The obtained angle is digitized as the value currently indicated by the analog gauge through a formula. It was confirmed from the experiments that the digitization of the analog gauge using image processing was successful, indicating the equivalent current value shown by the gauge. When applied to surveillance robots, this algorithm can minimize safety risks and time and opportunity costs of crew members for engine room surveillance.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.3
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• pp.111-118
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• 2023

MXene, a two-dimensional transition metal carbide or nitride, has recently attracted much attention as a lightweight and flexible electromagnetic shielding material due to its high electrical conductivity, good mechanical strength and thermal stability. In particular, the Ti-based MXene, Ti₃C₂T_x and Ti₂CT_x are reported to have the best electrical conductivity and electromagnetic shielding properties in the vast MXene family. Therefore, in this study, Ti₃C₂T_x and Ti₂CT_x films were prepared by vacuum filtration using Ti₃C₂T_x and Ti₂CT_x dispersions synthesized by interlayer metal etching and centrifugation of Ti₃AlC₂ and Ti₂AlC. The electrical conductivity and electromagnetic shielding efficiency of the films were measured after heat treatment at high temperature. Then, X-ray diffraction and photoelectron spectroscopy were performed to analyze the structural changes of Ti₃C₂T_x and Ti₂CT_x films after heat treatment and their effects on electromagnetic shielding. Based on the results of this study, we propose an optimal structure for an ultra-thin, lightweight, and high performance MXene-based electromagnetic shielding film for future applications in small and wearable electronics.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.91-98
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• 2023

The amount of power generation of a solar plant has a high correlation with weather conditions, geographical conditions, and the installation conditions of solar panels. Previous studies have found the elements which impacts the amount of power generation. Some of them found the optimal conditions for solar panels to generate the maximum amount of power. Considering the realistic constraints when installing a solar power plant, it is very difficult to satisfy the conditions for the maximum power generation. Therefore, it is necessary to know how sensitive the solar power generation amount is to factors affecting the power generation amount, so that plant owners can predict the amount of solar power generation when examining the installation of a solar power plant. In this study, we propose a polynomial regression analysis method to analyze the relationship between solar power plant's power generation and related factors such as weather, location, and installation conditions. Analysis data were collected from 10 solar power plants installed and operated in Daegu and Gyeongbuk. As a result of the analysis, it was found that the amount of power generation was affected by panel type, amount of insolation and shade. In addition, the power generation was affected by interaction of the installation angle and direction of the panel.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.165-184
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• 2023

Recently, Deep learning analysis of unstructured text data using language models, such as Google's BERT and OpenAI's GPT has shown remarkable results in various applications. Most language models are used to learn generalized linguistic information from pre-training data and then update their weights for downstream tasks through a fine-tuning process. However, some concerns have been raised that privacy may be violated in the process of using these language models, i.e., data privacy may be violated when data owner provides large amounts of data to the model owner to perform fine-tuning of the language model. Conversely, when the model owner discloses the entire model to the data owner, the structure and weights of the model are disclosed, which may violate the privacy of the model. The concept of offsite tuning has been recently proposed to perform fine-tuning of language models while protecting privacy in such situations. But the study has a limitation that it does not provide a concrete way to apply the proposed methodology to text classification models. In this study, we propose a concrete method to apply offsite tuning with an additional classifier to protect the privacy of the model and data when performing multi-classification fine-tuning on Korean documents. To evaluate the performance of the proposed methodology, we conducted experiments on about 200,000 Korean documents from five major fields, ICT, electrical, electronic, mechanical, and medical, provided by AIHub, and found that the proposed plug-in model outperforms the zero-shot model and the offsite model in terms of classification accuracy.

• Membrane Journal
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• v.34 no.2
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• pp.154-162
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• 2024

Anion exchange membranes (AEMs) are essential components in water electrolysis systems, serving to physically separate the generated hydrogen and oxygen gases while enabling the selective transport of hydroxide ions between electrodes. Key characteristics sought in AEMs include high ion conductivity and robust chemical and mechanical stability in alkaline. In this study, quaternized Poly(terphenyl piperidinium)/cellulose nanocrystals (qPTP/CNC) mixed matrix membrane was fabricated. The polymer matrix, PTP, was synthesized via super-acid polymerization, known for its excellent ion conductivity and alkaline durability. The qPTP/CNC membrane showed a dense and uniform morphology without significant voids or large aggregates at the polymer-nanoparticle interface. The qPTP/CNC membrane containing 2 wt% CNC demonstrated a high ion exchange capacity of 1.90 mmol/g, coupled with low water uptake (9.09%) and swelling ratio (5.56%). Additionally, the qPTP/CNC membrane showed significantly lower resistance and superior alkaline stability (384 hours at 50℃ in 1 M KOH) compared to the commercial FAA-3-50 membrane. These results highlight the potential of hydrophilic additive CNC in enhancing ion conductivity and alkaline durability of ion exchange membranes.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.2
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• pp.55-68
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• 2024

Plant engineering companies create or refer to requirements documents for each related field, such as plant process/equipment/piping/instrumentation, in different engineering departments. The process-related requirements document includes not only a description of the process but also the requirements of the equipment or related facilities that will operate it. Since the authors and reviewers of the requirements documents are different, there is a possibility that inconsistencies may occur between equipment or parts design specifications described in different requirement documents. Ensuring consistency in these matters can increase the reliability of the overall plant design information. However, the amount of documents and the scattered nature of requirements for a same equipment and parts across different documents make it challenging for engineers to trace and manage requirements. This paper proposes a method to analyze requirement sentences and calculate the similarity of requirement sentences in order to identify semantically identical sentences. To calculate the similarity of requirement sentences, we propose a named entity recognition method to identify compound words for the parts and properties that are semantically central to the requirements. A method to calculate the similarity of the identified compound words for parts and properties is also proposed. The proposed method is explained using sentences in practical documents, and experimental results are described.

• Journal of the Korean Geotechnical Society
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• v.40 no.1
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• pp.5-14
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• 2024

PHC piles demonstrate superior resistance to compression and bending moments, and their factory-based production enhances quality assurance and management processes. Despite these advantages that have resulted in widespread use in civil engineering and construction projects, the design process frequently relies on empirical formulas or N-values to estimate the soil-pile friction, which is crucial for bearing capacity, and this reliance underscores a significant lack of experimental validation. In addition, environmental factors, e.g., the pH levels in groundwater and the effects of seawater, are commonly not considered. Thus, this study investigates the influence of vibrating machine foundations on PHC pile models in consideration of the effects of varying pH conditions. Concrete model piles were subjected to a one-month conditioning period in different pH environments (acidic, neutral, and alkaline) and under the influence of seawater. Subsequent repeated direct shear tests were performed on the pile-soil interface, and the disturbed state concept was employed to derive parameters that effectively quantify the dynamic behavior of this interface. The results revealed a descending order of shear stress in neutral, acidic, and alkaline conditions, with the pH-influenced samples exhibiting a more pronounced reduction in shear stress than those affected by seawater.

• Composites Research
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• v.37 no.3
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• pp.238-245
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• 2024

In this study, as part of the development of a monitoring system for the efficient maintenance of steel pipes, an experimental study was conducted to evaluate the performance of steel pipes treated with modified polyethylene coating. In the case of the conventional mechanical pre-coating method, there was a deterioration in polyethylene adhesion during expansion testing, which led to the application of a chemical pre-treatment process using a calcium-mixed phosphate zinc film to resolve this issue. SEM and EDX analyses showed that the densest structure was observed at a Zn/Ca ratio of 1.0, and improved heat resistance compared to the conventional method was confirmed. Additionally, to prevent coating detachment during expansion, an evaluation of adhesion and elongation was conducted on steel pipes with modified polyethylene coating, incorporating materials such as elastomers based on maleic anhydride grafting, metal oxides, blocking agents, and slip agents. Experimental results showed that the specimen (S4) containing all modified materials exhibited more than a 25% performance improvement compared to the specimen (S2) containing only metal oxides. Lastly, the development and performance evaluation of wedge-shaped socketing and pressing wheels, which are part of the pipe fixing accessories, were conducted to prevent surface coating damage on the completed pipes.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.106-116
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• 2024

Purpose: This paper conducts IoT and CCTV-based safety monitoring to analyze accidents and potential risks occurring at construction sites, and detect and analyze risks such as falls and collisions or abnormalities and to establish a system for early warning using devices like a walkie-talkie and chatbot service. Method: A safety management service model is presented through smart construction technology case studies at the construction site and review a relevant literature analysis. Result: According to 'Construction Accident Statistics,' in 2021, there were 26,888 casualties in the construction industry, accounting for 26.3% of all reported accidents. Fatalities in construction-related accidents amounted to 417 individuals, representing 50.5% of all industrial accident-related deaths. This study suggests implementing AI chatbot services for construction site safety management utilizing IoT-based health monitoring technologies in smart construction practices. Construction sites where stakeholders such as workers participate were demonstrated by implementing an artificial intelligence chatbot system by selecting major risk areas within the workplace, such as scaffolding processes, openings, and access to hazardous machinery. Conclusion: The possibility of commercialization was confirmed by receiving more than 90 points in the satisfaction survey of participating workers regarding the empirical results of the artificial intelligence chatbot service at construction sites.