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Analysis of Infiltration Route using Optimal Path Finding Methods and Geospatial Information (지형공간정보 및 최적탐색기법을 이용한 최적침투경로 분석)

  • Bang, Soo Nam;Heo, Joon;Sohn, Hong Gyoo;Lee, Yong Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1D
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    • pp.195-202
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    • 2006
  • The infiltration route analysis is a military application using geospatial information technology. The result of the analysis would present vulnerable routes for potential enemy infiltration. In order to find the susceptible routes, optimal path search algorithms (Dijkstra's and $A^*$) were used to minimize the cost function, summation of detection probability. The cost function was produced by capability of TOD (Thermal Observation Device), results of viewshed analysis using DEM (Digital Elevation Model) and two related geospatial information coverages (obstacle and vegetation) extracted from VITD (Vector product Interim Terrain Data). With respect to 50m by 50m cells, the individual cost was computed and recorded, and then the optimal infiltration routes was found while minimizing summation of the costs on the routes. The proposed algorithm was experimented in Daejeon region in South Korea. The test results show that Dijkstra's and $A^*$ algorithms do not present significant differences, but A* algorithm shows a better efficiency. This application can be used for both infiltration and surveillance. Using simulation of moving TOD, the most vulnerable routes can be detected for infiltration purpose. On the other hands, it can be inversely used for selection of the best locations of TOD. This is an example of powerful geospatial solution for military application.

Evaluation of Bonding Performance in UHPC-based Concrete Repair Materials Considering Surface of Structure Subject to Repair (보수대상 구조 표면 상태를 고려한 UHPC 기반 콘크리트 보수재료의 부착 성능 평가)

  • Yong-Sik Yoon;Kyong-Chul Kim;Kwang-Mo Lim;Gi-Hong An;Gum-Sung Ryu;Kyung-Taek Koh
    • Journal of the Korean Recycled Construction Resources Institute
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    • v.11 no.4
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    • pp.433-439
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    • 2023
  • In this study, the bonding performance of repair materials was evaluated on concrete repair surface to develop concrete repair materials based on UHPC (Ultra High Performance Concrete) which has high mechanical and durability performance. The ten test variables were applied considering the roughness and wet condition of the concrete surface subject to repair, the addition of polymer, and the use PP and PVA fibers in repair materials. The addition of the polymer caused a significant decrease in strength, which was thought to be due to the effect of the additional super plasticizer used to adjust workability. Also, flow was reduced by up to 13.8 % with the use of plastic-based fibers. As a result of evaluating the bond strength of the repair material considering the condition of the surface subject to repair, it was thought that in the case of using UHPC-based repair material, high bonding performance could be secured without any additional surface treatment as long as the surface of the base material was sound. In addition, UHPC-based repair materials showed high bonding performance even when the attachment surface was wet. In the future, research will be conducted on shot-crete application and gradient pouring for the development of UHPC-based repair materials, and continuous improvement in the repair material mixing property will be carried out to ensure economic efficiency and performance as a concrete structural repair material.

Phase Segmentation of PVA Fiber-Reinforced Cementitious Composites Using U-net Deep Learning Approach (U-net 딥러닝 기법을 활용한 PVA 섬유 보강 시멘트 복합체의 섬유 분리)

  • Jeewoo Suh;Tong-Seok Han
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.36 no.5
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    • pp.323-330
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    • 2023
  • The development of an analysis model that reflects the microstructure characteristics of polyvinyl alcohol (PVA) fiber-reinforced cementitious composites, which have a highly complex microstructure, enables synergy between efficient material design and real experiments. PVA fiber orientations are an important factor that influences the mechanical behavior of PVA fiber-reinforced cementitious composites. Owing to the difficulty in distinguishing the gray level value obtained from micro-CT images of PVA fibers from adjacent phases, fiber segmentation is time-consuming work. In this study, a micro-CT test with a voxel size of 0.65 ㎛3 was performed to investigate the three-dimensional distribution of fibers. To segment the fibers and generate training data, histogram, morphology, and gradient-based phase-segmentation methods were used. A U-net model was proposed to segment fibers from micro-CT images of PVA fiber-reinforced cementitious composites. Data augmentation was applied to increase the accuracy of the training, using a total of 1024 images as training data. The performance of the model was evaluated using accuracy, precision, recall, and F1 score. The trained model achieved a high fiber segmentation performance and efficiency, and the approach can be applied to other specimens as well.

Transfer Learning based DNN-SVM Hybrid Model for Breast Cancer Classification

  • Gui Rae Jo;Beomsu Baek;Young Soon Kim;Dong Hoon Lim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.11
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    • pp.1-11
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    • 2023
  • Breast cancer is the disease that affects women the most worldwide. Due to the development of computer technology, the efficiency of machine learning has increased, and thus plays an important role in cancer detection and diagnosis. Deep learning is a field of machine learning technology based on an artificial neural network, and its performance has been rapidly improved in recent years, and its application range is expanding. In this paper, we propose a DNN-SVM hybrid model that combines the structure of a deep neural network (DNN) based on transfer learning and a support vector machine (SVM) for breast cancer classification. The transfer learning-based proposed model is effective for small training data, has a fast learning speed, and can improve model performance by combining all the advantages of a single model, that is, DNN and SVM. To evaluate the performance of the proposed DNN-SVM Hybrid model, the performance test results with WOBC and WDBC breast cancer data provided by the UCI machine learning repository showed that the proposed model is superior to single models such as logistic regression, DNN, and SVM, and ensemble models such as random forest in various performance measures.

A Study on Energy Savings of a DC-based Variable Speed Power Generation System (직류기반 가변속 발전 시스템을 이용한 에너지 절감에 관한 연구)

  • Kido Park;Gilltae Roh;Kyunghwa Kim;Changjae Moon;Jongsu Kim
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.6
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    • pp.666-671
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    • 2023
  • As international environmental regulations on ship emissions are gradually strengthened, interest in electric propulsion and hybrid propulsion ships is increasing, and various solutions are being developed and applied to these ships, especially stabilization of the power system and system efficiency. The direct current distribution system is being applied as a way to increase the power. In addition, verification and testing of safety and performance of marine DC distribution systems is required. As a result of establishing a DC distribution test bed, verifying the performance of the DC distribution (variable speed power generation) system, and analyzing fuel consumption, this study applied a variable speed power generation system that is applied to DC power distribution for ships, and converted the power output from the generator into a rectifier. A system was developed to convert direct current power to connect to the system and monitor and control these devices. Through tests using this DC distribution system, the maximum voltage was 751.5V and the minimum voltage was 731.4V, and the voltage fluctuation rate was 2.7%, confirming that the voltage is stably supplied within 3%, and a variable speed power generation system was installed according to load fluctuations. When applied, it was confirmed through testing that fuel consumption could be reduced by more than 20% depending on the section compared to the existing constant speed power generation system.

Application of Back Analysis Technique Based on Direct Search Method to Estimate Tension of Suspension Bridge Hanger Cable (현수교 행어케이블의 장력 추정을 위한 직접탐색법 기반의 역해석 기법의 적용 )

  • Jin-Soo Kim;Jae-Bong Park;Kwang-Rim Park;Dong-Uk Park;Sung-Wan Kim
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.5
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    • pp.120-129
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    • 2023
  • Hanger cable tension is a major response that can determine the integrity and safety of suspension bridges. In general, the vibration method is used to estimate hanger cable tension on operational suspension bridges. It measures natural frequencies from hanger cables and indirectly estimates tension using the geometry conditions of the hanger cables. This study estimated the hanger cable tension of the Palyeong Bridge using a vision-based system. The vision-based system used digital camcorders and tripods considering the convenience and economic efficiency of measurement. Measuring the natural frequencies for high-order modes required for the vibration method is difficult because the hanger cable response measured using the vision-based system is displacement-based. Therefore, this study proposed a back analysis technique for estimating tension using the natural frequencies of low-order modes. Optimization for the back analysis technique was performed by defining the difference between the natural frequencies of hanger cables measured in the field and those calculated using finite element analysis as the objective function. The direct search method that does not require the partial derivatives of the objective function was applied as the optimization method. The reliability and accuracy of the back analysis technique were verified by comparing the tension calculated using the method with that estimated using the vibration method. Tension was accurately estimated using the natural frequencies of low-order modes by applying the back analysis technique.

Evaluation of Validity Thyroid Scintigraphy Using Parallel Hole Collimator (갑상샘 신티그래피 검사 시 평행다공형 조준기 적용의 유효성 평가)

  • Su-Young Park;Ji-Youn Kim;Sung-Min Ahn
    • Journal of the Korean Society of Radiology
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    • v.18 no.1
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    • pp.27-36
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    • 2024
  • In this study, When acquisition thyroid scintigraphy images, a parallel hole collimator was applied, and the difference from the pinhole collimator was quantitatively analyzed under each image acquisition condition. Visual size, resolution, sensitivity, signal to noise ratio (SNR), and contrast to noise ratio (CNR) were evaluated using thyroid phantom and point source. When comparing visual size, it was confirmed that an image similar to the size of the pinhole collimator could be obtained only when a magnification ratio of about 2.00 to 2.09 times when applying a parallel hole collimator. There was no tendency in FWHM(mm) measurement using a point source, and sensitivity was high in the parallel hole collimator. SNR and CNR were high when using a low magnification ratio, matrix size of 128×128, and a parallel hole collimator. In images of similar size to the naked eye, when the matrix size was the same, both SNR and CNR were high in the pinhole collimator. Therefore, when performing a thyroid scintigraphy test, if appropriate conditions are set according to the situation of each hospital and a parallel hole collimator is applied, it can be a good option in terms of equipment utilization and work efficiency.

A Case Study on Metadata Extractionfor Records Management Using ChatGPT (챗GPT를 활용한 기록관리 메타데이터 추출 사례연구)

  • Minji Kim;Sunghee Kang;Hae-young Rieh
    • Journal of Korean Society of Archives and Records Management
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    • v.24 no.2
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    • pp.89-112
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    • 2024
  • Metadata is a crucial component of record management, playing a vital role in properly managing and understanding the record. In cases where automatic metadata assignment is not feasible, manual input by records professionals becomes necessary. This study aims to alleviate the challenges associated with manual entry by proposing a method that harnesses ChatGPT technology for extracting records management metadata elements. To employ ChatGPT technology, a Python program utilizing the LangChain library was developed. This program was designed to analyze PDF documents and extract metadata from records through questions, both with a locally installed instance of ChatGPT and the ChatGPT online service. Multiple PDF documents were subjected to this process to test the effectiveness of metadata extraction. The results revealed that while using LangChain with ChatGPT-3.5 turbo provided a secure environment, it exhibited some limitations in accurately retrieving metadata elements. Conversely, the ChatGPT-4 online service yielded relatively accurate results despite being unable to handle sensitive documents for security reasons. This exploration underscores the potential of utilizing ChatGPT technology to extract metadata in records management. With advancements in ChatGPT-related technologies, safer and more accurate results are expected to be achieved. Leveraging these advantages can significantly enhance the efficiency and productivity of tasks associated with managing records and metadata in archives.

Mechanical Properties of Fiber-reinforced Cement Composites according to a Multi-walled Carbon Nanotube Dispersion Method (다중벽 탄소나노튜브의 분산방법에 따른 섬유보강 시멘트복합체의 역학적 특성)

  • Kim, Moon-Kyu;Kim, Gyu-Yong;Pyeon, Su-Jeong;Choi, Byung-Cheol;Lee, Yae-Chan;Nam, Jeong-Soo
    • Journal of the Korea Institute of Building Construction
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    • v.24 no.2
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    • pp.203-213
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    • 2024
  • This study delves into the mechanical properties of fiber-reinforced cement composites(FRCC) concerning the dispersion method of multi-walled carbon nanotubes(MWCNTs). MWCNTs find utility in industrial applications, particularly in magnetic sensing and crack detection, owing to their diverse properties including heat resistance and chemical stability. However, current research endeavors are increasingly directed towards leveraging the electrical properties of MWCNTs for self-sensing and smart sensor development. Notably, achieving uniform dispersion of MWCNTs poses a challenge due to variations in researchers' skills and equipment, with excessive dispersion potentially leading to deterioration in mechanical performance. To address these challenges, this study employs ultrasonic dispersion for a defined duration along with PCE surfactant, known for its efficacy in dispersion. Test specimens of FRCC are prepared and subjected to strength, drawing, and direct tensile tests to evaluate their mechanical properties. Additionally, the influence of MWCNT dispersion efficiency on the enhancement of FRCC mechanical performance is scrutinized across different dispersion methods.

Effect of Bulnesia sarmienti Single and Complex Extracts on Serum Lipid and Body Fat in Rats Fed High-fat Diet (고지방식이를 섭취한 흰쥐에서 Bulnesia sarmienti 단일추출물과 복합추출물이 혈청지질 및 체지방에 미치는 영향)

  • Park, Chang-Ho;Kim, Dae-Ik;Jung, Hee-Kyoung;Lee, Gee-Dong;Kim, Kil-Soo;Hong, Joo-Heon
    • Korean Journal of Food Science and Technology
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    • v.40 no.4
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    • pp.449-454
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    • 2008
  • This research examined whether feeding single extracts or complex extracts of Bulnesia sarmienti, together with a high fat diet, could improve serum lipid levels and reduce fat mass in rats. Test groups were fed the extracts, combined with a high fat diet, for eight weeks, and subdivided into seven groups: normal, control, and five treatment groups (BS: B. sarmienti extracts; BS-S: B. sarmienti and Salvia miltiorrhiza Bunge extracts; BS-M: B. sarmienti and Morus alba Linne extracts; BS-SM1: B. sarmienti, Salvia miltiorrhiza Bunge and Morus alba Linne extracts; and BS-SM2: BS-SM1 extracts at a 2-fold concentration). After feeding the test substance for 8 weeks, no significant differences were found for food intake, water intake, change in body weight, or food efficiency ratios (FER) among the groups. However, serum LDL-cholesterol had increased by 14.1% in the BS-S group. When compared with the control group, total cholesterol levels in the BS, BS-S, BS-M, BS-SM1, and BS-SM2 groups were reduced by 36.0, 14.5, 40.4, 17.5, and 22.5%, respectively, with the greatest change shown in the BS-M group. In terms of triglycerides, levels in BS, BS-S, BS-M, BS-SM1, and BS-SM2 had decreased by 41.9, 8.5, 62.3, 17.7, and 14.5%, respectively. Compared to the control group, the BS group showed a significant decrease in fat mass. In conclusion, the BS and BS-M groups showed significant effects with respect to improved serum lipid profiles and body fat mass when they were fed a high fat diet in combination with the respective extracts.