• Journal of the Korean Society of Radiology
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• v.16 no.2
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• pp.103-113
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• 2022

In this paper, a combined ¹⁸F-FDG(fluorodeoxyglucose) and MNP(magnetic nanoparticles) contrast agent was synthesized using N-(p-maleimidophenyl) isocyanate as the crosslinker for use in simultaneous PET-MRI scans. PET-MRI images were acquired and evaluated before and after injection of the combined contrast imaging agent (¹⁸F-FDG labeled MNP) from a glioma stem cell mouse model. After setting the region of interest (ROI) on each acquired image, the area of the lesion was calculated by segmentation. As a result, the PET image was larger than the MRI. In particular, the simultaneous PET-MRI images showed accurate lesions along with the surrounding soft tissue. The mean and standard deviation values were higher in the MRI images alone than in the PET images or the simultaneous PET-MRI images, regardless of whether the contrast agent was injected. In addition, the simultaneous PET-MRI image values were higher than for the PET images. For PSNR experiments, the original image was PET Image using 18F-FDG, MRI using MNPs, and MRI without contrast medium, and the target image was simultaneous PET-MRI image using 18F-FDG labeled MNPs contrast medium. As a result, all of them appeared significantly, suggesting that the 18F-FDG labeled MNPs contrast medium is useful. Future research is needed to develop an agent that can simultaneously diagnose and treat through SPECT-MRI imaging research that can use various nuclides.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.453-462
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• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.77-82
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• 2023

The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.

• 한국노년학
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• v.31 no.2
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• pp.381-400
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• 2011

The purpose of this study is to develop the scale on Selection, Optimization, Compensation(SOC) model as successful aging strategies of Korean Elderly. In first phase of the study, 64 pilot items were collected from researcher's indepth interviews with a purposive sample group of 24 elderly people(16 items) and original SOC scale(48 items). To analyze the factor structure and to verify the validity of the scale, 592 questionnaires collected from survey were divided randomly into 300 developmental samples and 292 validity samples. The items were examined exploratory with developmental samples and confirmatory factor analysis with developmental samples. Two factor analysis supported four factor structure of the SOC consisted of 20 items. Four factors are as follows: 'Elective Selection', 'Loss-Based Selection', 'Opimization', 'Compensation'. The cronbach's alpha estimate of the scale was .930. This scale of four factor model exhibited good fit, assessed by overall fit measure criteria(TLI=.939, CFI=.947, RMSEA=.058). The result of analysis by item response theory for SOC scale is satisfatory. Also, SOC scale was significantly related to the two successful aging scales for Korean elderly and life satisfation scale(SWLS). These results proved the validity of the scale.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1321-1330
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• 2023

This study attempts to address the problem of 3D pose estimation for multiple human objects through a single image generated during the character development process that can be used in augmented reality. In the existing top-down method, all objects in the image are first detected, and then each is reconstructed independently. The problem is that inconsistent results may occur due to overlap or depth order mismatch between the reconstructed objects. The goal of this study is to solve these problems and develop a single network that provides consistent 3D reconstruction of all humans in a scene. Integrating a human body model based on the SMPL parametric system into a top-down framework became an important choice. Through this, two types of collision loss based on distance field and loss that considers depth order were introduced. The first loss prevents overlap between reconstructed people, and the second loss adjusts the depth ordering of people to render occlusion inference and annotated instance segmentation consistently. This method allows depth information to be provided to the network without explicit 3D annotation of the image. Experimental results show that this study's methodology performs better than existing methods on standard 3D pose benchmarks, and the proposed losses enable more consistent reconstruction from natural images.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.403-409
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• 2024

In this paper, the guidelines for the design of an Artificial Intelligence(AI) based Integrated Process Safety Management(PSM) system to enhance workplace safety using data from process safety reports submitted by hazardous and risky facility operators in accordance with the Occupational Safety and Health Act is proposed. The system composed of the proposed guidelines is to be implemented separately by individual facility operators and specialized process safety management agencies for single or multiple workplaces. It is structured with key components and stages, including data collection and preprocessing, expansion and segmentation, labeling, and the construction of training datasets. It enables the collection of process operation data and change approval data from various processes, allowing potential fault prediction and maintenance planning through the analysis of all data generated in workplace operations, thereby supporting decision-making during process operation. Moreover, it offers utility and effectiveness in time and cost savings, detection and prediction of various risk factors, including human errors, and continuous model improvement through the use of accurate and reliable training data and specialized datasets. Through this approach, it becomes possible to enhance workplace safety and prevent accidents.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.5
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• pp.57-75
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• 2011

The purpose of this study is to find ways of evaluating the suitability of sites being considered for development of different types of parks in the vicinity of yangmock-myun kyoung buk, where a large project(as large as about14.0$km^2$) has been planned. The results are as follows. Three surveys for selecting the assessment indicators were performed. ${\cdot}$ The first survey analyzed the importance of 23 selected assessment indicators based on a review of existing literature review and an on-the-spot research. ${\cdot}$ The second survey selected assessment indicators for each park type. ${\cdot}$ The third survey computed additive values of selected assessment indicators by the park types. It used a method of standardizing the average importance of indicators by making their sum equal to 10. These additive values were then multiplied by each grade of indicators to make a final evaluation. An evaluation of the site-suitability of park types was performed twice. The purpose of the first evaluation was to figure out how much each type met the minimum requirements targeted for all landscape types. The minimum requirements were derived by using a relative comparison between the standard of value rating of the assessment indicators, which was over the medium magnitude on the importance analysis, and the result of field research. A second evaluation estimated the targeted sites that met the minimum requirements. Value ratings of second assessment indicators were quantitatively divided as 1 to 3 grade and the evaluation scores were added, giving an additive value for each assessment indicator. The evaluation score on each park type was rated on a scale of 1 to 3 according to their averages, (from lowest to highest). Since this evaluation model of the site suitability on park types only focused on the 'face' of space in this study, additional analysis is necessary for setting the evaluation model and incorporating the overall impact of space, network connection and other factors, considering 'spot', 'line' and 'face' aspects of space.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.21-28
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• 2017

Practical models for FPGA architectures which include performance- and/or density-enhancing components such as carry chains, wide function multiplexers, and memory/multiplier blocks are being applied to academic FPGA placement tools which used to rely on simple imaginary models. Previously the techniques such as pre-packing and multi-layer density analysis are proposed to remedy issues related to such practical models, and the wire length is effectively minimized during initial analytic placement. Since timing should be optimized rather than wire length, most previous work takes into account the timing constraints. However, instead of the initial analytic placement, the timing-driven techniques are mostly applied to subsequent steps such as placement legalization and iterative improvement. This paper incorporates the timing driven techniques, which check if the placement meets the timing constraints given in the standard SDC format, and minimize the detected violations, with the existing analytic placer which implements pre-packing and multi-layer density analysis. First of all, a static timing analyzer has been used to check the timing of the wire-length minimized placement results. In order to minimize the detected violations, a function to minimize the largest arrival time at end points is added to the objective function of the analytic placer. Since each clock has a different period, the function is proposed to be evaluated for each clock, and added to the objective function. Since this function can unnecessarily reduce the unviolated paths, a new function which calculates and minimizes the largest negative slack at end points is also proposed, and compared. Since the existing legalization which is non-timing driven is used before the timing analysis, any improvement on timing is entirely due to the functions added to the objective function. The experiments on twelve industrial examples show that the minimum arrival time function improves the worst negative slack by 15% on average whereas the minimum worst negative slack function improves the negative slacks by additional 6% on average.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• The korean journal of orthodontics
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• v.36 no.1 s.114
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• pp.55-62
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• 2006

Orthodontic mini-implants, despite its usefulness as anchorage, have some limits such as loosening. Therefore, various shapes and lengths have been studied. The aim of this study is to analyze the shape and length of mini-implants mechanically. The shapes of mini-implants (1.6 mm, Dual Top, Jeil Medical Co., Seoul, Korea) were cylindrical and taper. The lengths of mini-implants were 6 mm and 8 mm. The tested groups were 5 groups (cylindrical 6 mm, cylindrical 8 mm, taper 6 mm, taper 8 mm and taper 8 mm modified whose thread is reduced from the middle to upper part). All were inserted and removed on the polyurethane foam with the torque measured. During insertion and removal, the taper shape needed higher torque than the cylindrical shape, and the 8 mm length than the 6 mm length (p<0.001). The taper 6mm group showed superior insertion torque (p<0.001) and similar removal torque to the cylindrical 8 mm group. The taper 8 mm modified group with gradually reduced threads, showed continuous high removal torque after the peak. The initial mechanical stability can be provided by the tapered shape and also, affected by length and thread design.