• Journal of the Korean Geosynthetics Society
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• v.10 no.4
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• pp.81-92
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• 2011

In order to understand evaluation of the seismic stability of a fill dam, we made chambers of 1:100, 1:70, and 1:50 (the ratio of the miniature), considering the law of similarity based on drawings of three representative cross sections. And we measured an increase in acceleration, excess pore water pressure, and vertical/horizontal displacement after applying Hachinohe wave (long period), Ofunato wave (short period), and artificial wave, complying with the domestic standards, in order to evaluate the stability and interaction between the ground, the structure, and fluids based on the measurements. As a result, we could observe that displacement of the target cross section was relatively small compared to the allowed level of 30 cm, ensuring proper stability for an earthquake. Regarding the acceleration measurements, the increase rate was 20% for Hachinohe wave and Ofunato wave but 30% for the artificial wave. With respect to the excess pore water pressure, it was lower than 1 (which is the permissible ratio for liquefaction) ensuring proper stability as well.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.8
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• pp.3587-3592
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• 2014

Burden of cancer is progressively increasing in developing countries like India which has also led to a steep rise in toxicity due to anti-cancer therapy. A cross-sectional analysis was here conducted for patients with different malignancies (except leukaemia) who while undergoing radical anti-cancer therapy were admitted to our oncology ward from January-July 2013. In a total of 280 patients, the total number of toxicity events was 473. Nine patients expired over this time period. Among the events, grade 2 anaemia the most common (n=189) while the most common grades of neutropenia and thrombocytopenia were grade 4 (n=114) and grade 2 (n=48), respectively. Among the tracable microbial etiologies, gram negative bacteria were the most commonly found pathogens. Treatment interruptions took place in 240 patients (median duration=8.8 days). Prolonged hospital admission, intensive care and artificial ventilation support was needed to be given in 48, 7 and 13 patients respectively. Advanced NSCLC, KPS <70, pancytopenia and artificial ventilation requirement were found to have a significant impact on death. Such studies show the prevailing practice from institutes of our country and may guide us formulating a guideline for managing such toxicities for this part of the world.

• Journal of Korean Society on Water Environment
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• v.33 no.3
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• pp.291-301
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• 2017

This study was carried out to investigate distribution on the alien plants in the Gyeong-in Ara Waterway. The alien plants were a total of 82 taxa: 17 families, 63 genera, 80 species, and 2 varieties. This number corresponds to 25.5% of alien plants identified in Korea. The proportion of alien plants in every year was increased from upstream to downstream. As the result of the analysis on vegetation stratification, bank of waterside was covered with artificial materials preventing existence of vegetation, and had step-type cross section. Floodplain was composed of waterfront area. An array of vegetation was not typical dispersion, and terrestrial and alien plants were dominated the Gyeong-in Ara Waterway. Evaluation of naturalness based on the vegetation stratification showed grade 3 or 4. In order to solve a problem, method and level of restoration should be decided based on the result of diagnostic assessment. Therefore, we need to restore the step-type cross section as pool type one. From waterside to bank in this waterway, we recommend to introduce natural plants by imitating reference species composition. Since, an invasion of alien plants is expected to be accelerated due to the continuous artificial disturbance, we recommend to quantitative investigation on the invasion of alien plants and monitoring on the change of distribution.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.51-57
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• 2021

In this paper, we propose a method to find the DoF(Depth of field) that is blurred in an image by focusing and out-focusing the camera through a efficient convolutional neural network. Our approach uses the RGB channel-based cross-correlation filter to efficiently classify the DoF region from the image and build data for learning in the convolutional neural network. A data pair of the training data is established between the image and the DoF weighted map. Data used for learning uses DoF weight maps extracted by cross-correlation filters, and uses the result of applying the smoothing process to increase the convergence rate in the network learning stage. The DoF weighted image obtained as the test result stably finds the DoF region in the input image. As a result, the proposed method can be used in various places such as NPR(Non-photorealistic rendering) rendering and object detection by using the DoF area as the user's ROI(Region of interest).

• Journal of Korea Water Resources Association
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• v.54 no.3
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• pp.203-215
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• 2021

In the present study, hydrologic data and topographical data from 2010 to 2019 were collected from three gauging stations placed in the watershed of Naeseong stream to determine changes and rates of changes in rainfall, water level & mean velocity, and water level & discharge, together with changes in rates of erosion and deposition at cross-sections of the river. Besides, effects of regulated and non-regulated rivers according to the presence of artificial regulation of flow rate of the river via artificial structure located at Seo stream (Yeongju si (Wolhogyo) station), the tributary free from construction of dams, were compared and analyzed. Results of analyses conducted in the present study revealed vegetational establishment and landforming due to increasing area of vegetational sandbar evolved in the flood plain (intermediate- or high- water level) by the drought sustained from 2013 to 2015. Continuous erosion of river bed was appeared because of narrowed flow area with low water level and increased velocity and tractive force on river bed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1046-1052
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• 2021

Artificial intelligence is being applied in various industrial fields to the development of the fourth industry and the construction of high-performance computing environments. In the medical field, deep learning learning such as cancer, COVID-19, and bone age measurement was performed using medical images such as X-Ray, MRI, and PET and clinical data. In addition, ICT medical fusion technology is being researched by applying smart medical devices, IoT devices and deep learning algorithms. Among these techniques, medical image-based deep learning learning requires accurate finding of medical image biomarkers, minimal loss rate and high accuracy. Therefore, in this paper, we would like to compare and analyze the performance of the Cross-Entropy function used in the image classification algorithm of the loss function that derives the loss rate in the chest X-Ray image-based deep learning learning process.

• Steel and Composite Structures
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• v.51 no.4
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• pp.441-456
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• 2024

This paper aims to develop Machine Learning (ML) algorithms to predict the buckling resistance of cold-formed steel (CFS) channels with restrained flanges, widely used in typical CFS sheathed wall panels, and provide practical design tools for engineers. The effects of cross-sectional restraints were first evaluated on the elastic buckling behaviour of CFS channels subjected to pure axial compressive load or bending moment. Feedforward multi-layer Artificial Neural Networks (ANNs) were then trained on different datasets comprising CFS channels with various dimensions and properties, plate thicknesses, and restraining conditions on one or two flanges, while the elastic distortional buckling resistance of the elements were determined according to the Finite Strip Method (FSM). To develop less biased networks and ensure that every observation from the original dataset has the chance of appearing in the training and test set, a K-fold cross-validation technique was implemented. In addition, the hyperparameters of the ANNs were tuned using a grid search technique to provide ANNs with optimum performances. The results demonstrated that the trained ANNs were able to predict the elastic distortional buckling resistance of CFS flange-restrained elements with an average accuracy of 99% in terms of coefficient of determination. The developed models were then used to propose a simple ANN-based design formula for the prediction of the elastic distortional buckling stress of CFS flange-restrained elements. Finally, the proposed formula was further evaluated on a separate set of unseen data to ensure its accuracy for practical applications.

• Journal of IKEEE
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• v.28 no.3
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• pp.405-411
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• 2024

In this paper, we have proposed VmCUnet, a deep learning model designed to enhance image segmentation performance in skin lesion image. VmCUnet has combined Vm-UnetV2 with the CIM(Cross-Scale Interaction Module), and the features extracted from each layer of the encoder have been integrated through CIM to accurately recognize the boundaries of various patterns and objects. VmCUnet has performed image segmentation of skin lesions using ISIC-2017 and ISIC-2018 datasets and has outperformed Unet, TransUnet, SwinUnet, Vm-Unet, and Vm-UnetV2 on the performance metrics IoU and Dice Score. In future work, we will conduct additional experiments on different medical imaging datasets to validate the generalization performance of the VmCUnet model.

• The Korean Journal of Pesticide Science
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• v.6 no.4
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• pp.264-270
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• 2002

Studies on the resistance monitoring of green peach ahpid, Myzus persicae, its development pattern by artificial selection with imidacloprid and cross-resistance were carried out to develope resistance management strategy. Resistance ratios of M. persicae collected at Hwachon and Dunnae among 5 locations in alpine cultivation area appeared to be high as 37.2 and 16.5, respectively. Resistance of aphid to imidacloprid developed slowly up to 20 time selection, and after that it grew quickly. Imidacloprid-resistant aphid strain showed low cross-resistance ratios(<10) to most of organophosphates, carbamates, and mixed insecticides except pirimicarb(487.8), but high ratios to acetamiprid(143.0) which is one of the neonicotinoids like imidacloprid, and pyrethroids such as deltamethrin(14.9), flucythrinate(12.9) and halothrin(15.9).

• Korean Journal of Medicinal Crop Science
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• v.16 no.5
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• pp.287-293
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• 2008

This study was conducted to determine the characteristics of fertilization process and embryo development of Astragalus membranaceus Bunge (Astragali Radix) to provide basic data needed in its breeding. A. membranaceus showed poor seed setting when self-pollination was induced. When artificial pollination was induced, it showed less than 5% bearing in late August, but more than 13% bearing from the beginning of September 4th. The flower size was about $17.0\;mm{\times}4.0\;mm$ and pistils and stamens had the same length of 15.0mm at flowering stage. When self-pollination or cross-pollination was induced, pollen tubes extended to an ovule. While pollen tube was extending to the ovule, reproductive cell split and formed two male generative nuclei and a vegetative nucleus. In the case of self-pollination, fertilized embryo was not observed, but was formed in the case of cross-pollination. A. membranaceus is noted to have zygote self-incompatibility. In the case of cross-pollination, fertilization was observed in 6 to 8 h after pollination, where apical cell derivatives split after fertilization. A spherical pro-embryo was then formed three days after fertilization. The seed attained full shape with a seed coat showing its distinctive contour 15 days after fertilization. Thus, A. membranaceus in Leguminosae family is found to have zygote selfincompatibility although its flower shape is shown to match the self-compatibility plant.