• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.5
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• pp.259-266
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• 2022

In this study, we developed a deep learning and vision sensor-based assembly performance evaluation method isfor prefabricated steel structures. The assembly parts were segmented using a modified version of the receptive field block convolution module inspired by the eccentric function of the human visual system. The quality of the assembly was evaluated by detecting the bolt holes in the segmented assembly part and calculating the bolt hole positions. To validate the performance of the evaluation, models of standard and defective assembly parts were produced using a 3D printer. The assembly part segmentation network was trained based on the 3D model images captured from a vision sensor. The sbolt hole positions in the segmented assembly image were calculated using image processing techniques, and the assembly performance evaluation using the k-nearest neighbor algorithm was verified. The experimental results show that the assembly parts were segmented with high precision, and the assembly performance based on the positions of the bolt holes in the detected assembly part was evaluated with a classification error of less than 5%.

• Particle and aerosol research
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• v.18 no.4
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• pp.137-145
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• 2022

As many studies on the harmfulness of fine dust have been reported, awareness of its seriousness is spreading. Recently, interest in indoor air quality as well as air pollution is increasing, and research on measures to block fine dust flowing into the room from the outside is being conducted. The clothing company is launching functional clothing to prevent fine dust attached to clothing from entering the room through outdoor activities. However, it is difficult to confirm whether there is actually fine-dust blocking performance, and there is no evaluation standard. In this study, the contamination rate caused by fine dust was quantitatively compared through image processing after contamination of the outer fabric for 4 types of commercially available functional clothing with fine-dust blocking effect. The difference in particle contamination according to the material of the outer fabric was analyzed by comparing the surface resistance, and it was found that the higher the surface resistance of the outer fabric material, the more fine dust was attached. The analysis method of this study is expected to be able to quantitatively compare and evaluate the fine-dust blocking performance of functional clothing.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.69-76
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• 2023

Hundreds of thousands of passwords are lost or forgotten every year, making the necessary information unavailable to legitimate owners or authorized law enforcement personnel. In order to recover such a password, a tool for password cracking is required. Using GPUs instead of CPUs for password cracking can quickly process the large amount of computation required during the recovery process. This paper optimizes on GPUs using CUDA, with a focus on decryption of the currently most popular PDF 1.4-1.6 version. Techniques such as eliminating unnecessary operations of the MD5 algorithm, implementing 32-bit word integration of the RC4 algorithm, and using shared memory were used. In addition, autotune techniques were used to search for the number of blocks and threads that affect performance improvement. As a result, we showed throughput of 31,460 kp/s (kilo passwords per second) and 66,351 kp/s at block size 65,536, thread size 96 in RTX 3060, RTX 3090 environments, and improved throughput by 22.5% and 15.2%, respectively, compared to the cracking tool hashcat that achieves the highest throughput.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.12
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• pp.419-428
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• 2022

Since in-place updates for pages are not allowed in flash memory, all new page writes should be written in an out-of-place manner. The old overwritten pages are invalidated. Such invalidated pages eventually trigger the costly garbage collection process. Since the garbage collection causes numerous read and write operations, it is one of the flash memory's major performance issues. In 2R, it modified the garbage collection algorithm, which applies the I/O characteristics of the On-Line Transaction Process workload to improve the Write Amplification Factor. However, this algorithm has a region pollution problem. Therefore, in this paper, we developed 2R++ that additionally separates pages with long access intervals to solve the region pollution problem. 2R++ introduces an extra bit per block to separate warm pages based on a second chance mechanism. Prevents warm pages from being misidentified as cold pages to solve region pollution problem. We conducted the experiments on TPC-C and Linkbench to make the performance comparison. The experiment showed that 2R++ achieved a Write Amplification Factor improvement of 57.8% and 13.8% compared to 2R, respectively.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.12
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• pp.429-436
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• 2022

Temporary files are generated when the Hash Join is performed on tables larger than the memory. During the join process, each temporary file is deleted sequentially after it completes the I/O operations. This paper reveals for that the fallocate system call and file deletion-related trim options significantly impact the hash join performance when temporary files are managed on SSDs rather than hard disks. The experiment was conducted on various commercial and research SSDs using PostgreSQL, a representative open-source database. We find that it is possible to improve the join performance up to 3 to 5 times compared to the default combination depending on whether fallocate and trim options are used for temporary files. In addition, we investigate the write amplification and trim command overhead in the SSD according to the combination of the two options for temporary files.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3268-3276
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• 2023

The practice of identifying the potential zones for mineral exploration in a speedy and low-cost method includes the use of satellite imagery analysis as a part of remote sensing techniques. It is challenging to explore the iron mineralization of a region through conventional methods which are a time-consuming process. The current study utilizes the Hyperion satellite imagery for mapping the iron mineralization and associated geological features in the Irikkur region, Kannur, Kerala. Along with the remote sensing results, the field study and laboratory-based analysis were conducted to retrieve the ground truth point and geochemical proportion to verify the iron ore mineralization. The MC simulation showed for shielding properties indicate an increase in the linear attenuation coefficient with raising the Fe₂O₃+SiO₂ concentrations in the investigated rocks where it is varied at 0.662 MeV in the range 0.190 cm^-1 - 0.222 cm^-1 with rising the Fe₂O₃+SiO₂ content from 57.86 wt% to 71.15 wt%. The analysis also revealed that when the γ-ray energy increased from 0.221 MeV to 2.506 MeV, sample 1 had the largest linear attenuation coefficient, ranging from 9.33 cm1 to 0.12 cm^-1. Charnockite rocks were found to have exceptional shielding qualities, making them an excellent natural choice for radiation shielding applications.

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

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.401-409
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• 2021

This study is a case study of artificial intelligence education subjects in the graduate school of education. The main educational contents consisted of understanding and practice of machine learning, data analysis, actual artificial intelligence using Entries, artificial intelligence and physical computing. As a result of the survey on the educational effect after the application of the curriculum, it was found that the students preferred the use of the Entry AI block and the use of the Blacksmith board as a physical computing tool as the priority applied to the elementary education field. In addition, the data analysis area is effective in linking math data and graph education. As a physical computing tool, Husky Lens is useful for scalability by using image processing functions for self-driving car maker education. Suggestions for desirable AI education include training courses by level and reinforcement of data collection and analysis education.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.3
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• pp.202-211
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• 2023

The profile shops in shipyards produce section steels required for block production of ships. Due to the limitations of shipyard's production capacity, a considerable amount of work is already outsourced. In addition, the need to improve the productivity of the profile shops is growing because the production volume is expected to increase due to the recent boom in the shipbuilding industry. In this study, a scheduling optimization was conducted for a parallel welding line of the profile process, with the aim of minimizing tardiness and the number of set-up changes as objective functions to achieve productivity improvements. In particular, this study applied a dynamic scheduling method to determine the job sequence considering variability of processing time. A Markov decision process model was proposed for the job sequence problem, considering the trade-off relationship between two objective functions. Deep reinforcement learning was also used to learn the optimal scheduling policy. The developed algorithm was evaluated by comparing its performance with priority rules (SSPT, ATCS, MDD, COVERT rule) in test scenarios constructed by the sampling data. As a result, the proposed scheduling algorithms outperformed than the priority rules in terms of set-up ratio, tardiness, and makespan.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.49-49
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• 2022

One of the major problems with sweetpotato (Ipomoea batats Lam.) is the tough thread tissue that occurs in the storage root, which has a negative impact on the sales of sweet potato because it impairs the texture during cooking and the processing quality. The fiber contents in storage roots of sweetpotato is affected by cultivation conditions and environment. To investigate the effect of fiber generation at different levels of irrigation, the sweetpoatoto "Hogammi" was transplanted in greenhouse. Sweetpotato was grown in styrofoam beds(W1605*D330*H300mm) to block moisture flowing from the outside. The irrigation was carried out as 3 levels (5,10, and 20 mm through drip irrigation facilities) at 20-day intervals. Five plants were harvested per plot at 90, 100 and 120 days after transplanting (DAT). The size of the storage root was large in the order of irrigation conditions 10mm>20mm>5mm treatment. And the longer cultivation period, the larger size of the storage root was observed. As a result of the analysis of the fiber content, it showed a tendency to decrease as the cultivation period increased (90days→120days). In addition, the fiber contents of sweetpotato harvested at 90, 100 and 120 DAT in the level of 5 mm irrigation plot were 351, 324 and 207 mg/100g, respectively, which were higher than those of other irrigation level plots. During all cultivation periods, the 10mm treatment group showed the lowest fiber content of 280, 228 and 127 mg/100g. At 20 mm irrigation level, the fiber content was less than that of 5mm irrigation level, but showed a tendency to increase compared to that of 10 mm irrigation level. These results suggested that drought stress or excessive-irrigation increases the fiber content of sweetpotato, which reduces their commercial value.