• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.10-18
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• 2024

Vehicle loading is one of the main causes of bridge deterioration. Although WiM (Weigh in Motion) can be used to measure vehicle loading on a bridge, it has disadvantage of high installation and maintenance cost due to its contactness. In this study, a non-contact method is proposed to estimate the vehicle loading history of bridges using deep learning and CCTV images. The proposed method recognizes the vehicle type using an object detection deep learning model and estimates the vehicle loading based on the load-based vehicle type classification table developed using the weights of empty vehicles of major domestic vehicle models. Faster R-CNN, an object detection deep learning model, was trained using vehicle images classified by the classification table. The performance of the model is verified using images of CCTVs on actual bridges. Finally, the vehicle loading history of an actual bridge was obtained for a specific time by continuously estimating the vehicle loadings on the bridge using the proposed method.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.71-86
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• 2023

Although starting a business plays a key role in strengthening national competitiveness and creating jobs, it is recognized as a risky choice. Failure to start a business can result in a wide range of negative effects, such as loss of personal wealth as well as deterioration of national competitiveness. This study considers startups that have reached a level of sustainable growth by achieving performance above the minimum profitability and sales standards for KOSDAQ listing, or achieved EXIT through sale or listing, as successful startups. based on the practical experiences of 23 successful entrepreneurs and Based on perception, the importance and priorities of startup success factors were derived through stratification analysis (Analytic Hierarchy Process, AHP), and interviews were conducted. In particular, using the ERIS model, we comprehensively analyze various variables of a start-up by considering the four elements of the entrepreneur, resources, industry, and strategy, and examine the changes and importance of success factors according to the characteristics of each growth stage of the start-up. As a goal, we specifically identified the challenges and opportunities faced by entrepreneurs at each stage. As a result of the study, the order of importance of the top factors of success factors in the start-up period was found to be the entrepreneur, resources, industry, and strategy. In particular, the importance of the entrepreneur's entrepreneurship spirit, special capabilities, general capabilities, and human resources was emphasized. The order of importance of the top factors of success factors during the growth period was found in the following order: entrepreneur, resources, industry, and strategy. In particular, the importance of general capabilities, entrepreneurship, and human and organizational resources was emphasized. This study is significant in that it analyzes startup success factors from the perspective of successful entrepreneurs and provides useful insights and directions to entrepreneurs and policy makers.

• Journal of the Korean Society of Radiology
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• v.18 no.2
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• pp.65-71
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• 2024

To achieve high resolution and sensitivity of positron emission tomography (PET) for small animals, the detector is constructed using very thin and long scintillation pixels. Due to the structure of these scintillation pixels, spatial resolution deterioration occurs outside the system's field of view. To solve this problem, we designed a detector that could improve spatial resolution by measuring the interaction depth and improve sensitivity by using a quasi-block scintillator. A quasi-block scintillator size of 12.6 mm x 12.6 mm x 3 mm was arranged in four layers, and optical sensors were placed on all sides to collect light generated by the interaction between gamma rays and the scintillator. DETECT2000 simulation was performed to evaluate the performance of the designed detector. Flood images were acquired by generating gamma-ray events at 1 mm intervals from 1.3 mm to 11.3 mm within the scintillator of each layer. The spatial resolution and peak-to-peak distance for each location were measured in an 11 x 11 array of flood images. The average measured spatial resolution was 0.25 mm, and the average distance between peaks was 1.0 mm. Through this, it was confirmed that all locations were separated from each other. In addition, because the light signals of all layers were measured separately from each other, the layer of the scintillator that interacted with the gamma rays could be completely separated. When the designed detector is used as a detector in a PET system for small animals, it is considered that excellent spatial resolution and sensitivity can be achieved and image quality can be improved.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.12-23
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• 2024

In this study, a structural concrete square beam was developed using the centrifugal molding technique. In order to secure the bending stiffness of the cross section, the hollow rate of the cross section was set to 10% or less. Instead of using the current poor mixture of concrete and a concrete mixing ratio with a high slump (150-200) and a design strength of 100 MPa or more was developed and applied. In order to investigate the durability of centrifugally formed PSC square beams to be used as the superstructure of the avalanch tunnel or ramen bridge, the durability performance of ultra-high-strength centrifugally formed concrete with a compressive strength of 100 MPa was evaluated in terms of deterioration and chemical resistance properties.Concrete durability tests, including chloride penetration resistance, accelerated carbonation, sulfate erosion resistance, freeze-thaw resistance, and scaling resistance, were performed on centrifugally formed square beam test specimens produced in 2022 and 2023. Considering the information verified in this study, the durability of centrifugally molded concrete, which has increased watertightness in the later manufacturing stage, was found to be superior to that of general concrete.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.209-223
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• 2024

In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.82-98
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• 2019

The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.

• Journal of the Korean Electrochemical Society
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• v.24 no.3
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• pp.65-75
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• 2021

Coin cell is a basic testing platform for battery research, discovering new materials and concepts, and contributing to fundamental research on next-generation batteries. Li metal batteries (LMBs) are promising since a high energy density (~500 Wh kg^-1) is deliverable far beyond Li-ion. However, Li dendrite-triggered volume fluctuation and high surface cause severe deterioration of performance. Given that such drawbacks are strongly dependent on the cell parameters and structure, such as the amount of electrolyte, Li thickness, and internal pressure, reliable Li metal coin cell testing is challenging. For the LMB-specialized coin cell testing platform, this study suggests the optimal coin cell structure that secures performance and reproducibility of LMBs under stringent conditions, such as lean electrolyte, high mass loading of NMC cathode, and thinner Li use. By controlling the cathode/anode (C/A) area ratio closer to 1.0, the inactive space was minimized, mitigating the cell degradation. The quantification and imaging of inner cell pressure elucidated that the uniformity of the pressure is a crucial matter to improving performance reliability. The LMB coin cells exhibit better cycling retention and reproducibility under higher (0.6 MPa → 2.13 MPa) and uniform (standard deviation: 0.43 → 0.16) stack pressure through the changes in internal parts and introducing a flexible polymer (PDMS) film.

• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.7
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• pp.1032-1042
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• 2011

The purpose of this study was to examine the attitudes and satisfaction level towards military foodservices as well as suggest effective ways to increase foodservice quality. A questionnaire survey was administered to 413 subjects, which included 400 soldiers and 13 foodservice managers. The survey period was from August 6 to August 25, 2008. The collected data were statistically treated using SPSS V12.0. Most of the investigated soldiers were 20~25 years old. The foodservice managers were male general officials and the majority of them had no prior food service training. None of the foodservice managers had a dietician certificate. Menu was planned through a local foodservice conference, and most food materials were delivered in the form of center-type and military unit-type. Deficiency and deterioration of food service facilities (28.6%) as well as deficiency in the number of cooking personnel (14.3%) increased the difficulty of operational management. Soldiers expressed a desire for increases in Western (25.7%) and Korean traditional foods (21.5%), which meant menu diversity. To increase the quality of military foodservices, taste of food (40.6%), increased portion size (30.4%), and improvement in hygienic conditions (13.6%) were demanded by the soldiers. Food taste (30.8%), improvement in hygienic conditions (23.1%), and better job management were all demanded by the foodservice managers. After factor analysis, quality attributes were rearranged into five dimensions, including facilities, food, menu, service, and sanitation most attributes were over 4 points out of 5 total in importance, but only 3 points in performance. The importance score was higher than the performance score. Soldiers' overall satisfaction level was on average 3.43 points out of 5 points.

• Journal of Yeungnam Medical Science
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• v.16 no.2
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• pp.208-218
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• 1999

Background: Lung cancer-associated hypercalcemia is one of the most disabling and life-threatening paraneoplastic disorders. Humoral hypercalcemia is responsible for most lung cancer-associated hypercalcemia. Patients with hypercalcemia are usually in the advanced stage with obvious bulky tumor and carry a poor prognosis. Materials and Methods: Total 29 patients satisfied the following criteria: histologically proven primary lung cancer, corrected calcium level ${\geq}$ 10.5 mg/dL, and symptoms which could possibly be attributed to hypercalcemia. In this retrospective study, we evaluated the various clinical aspects of hypercalcemia, in relation to cancer stage, histologic cell type, mass size, bone metastasis, performance status, and other possible characteristics. Results: Total 29 lung cancer patients with hypercalcemia were studied, and most of them had squamous cell carcinoma in their histologic finding. The incidence of hypercalcemia was significantly higher between 50 and 69 years of age, and in the advancement of cancer stage. Although serum calcium level showed positive correlation with mass size, performance status, and bone metastasis, it was not significant statistically. Altered consciousness was significantly more frequent in the patients with higher serum calcium level. There were no differences in effectiveness among therapeutic regimens. Hypercalcemia was more frequently in the later stage of disease than during the initial diagnosis of lung cancer. Most of the patients died within 1 month after development of hypercalcemia. Conclusion: We concluded that hypercalcemia in lung cancer is related to extremely poor prognosis, and may be one of the causes of death and should be treated aggressively to prevent sudden deterioration or death.

• Management & Information Systems Review
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• v.38 no.4
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• pp.25-39
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• 2019

The purpose of this study is to analyze the management performance of hospitals by analyzing the ratio of stability, profitability ratio, and growth rate through the financial ratios of medical institutions using accounting information disclosure data of medical institutions, financial status table and profit and loss statement. The main goal is to analyze and analyze financial statements of medical institutions' accounting information in 2016 and 2017, analyze the difference and analyze the general characteristics and financial ratios by type, type and size of medical institutions, The financial characteristics of medical institutions were identified. The ratio of stability, profitability, and growth rate through financial ratios were compared and analyzed. In addition, we analyzed the correlation between the medical profit margin, the total asset profit margin, the medical profit margin rate, and the net profit margin of the medical institutions through the financial ratios of accounting information disclosure data of medical institutions. The main results are as follows: First, the size of the hospital and the size of the debt through the change of assets, liabilities and capital of the financial statement are increasing, the size of own capital is relatively decreased, and the management performance is getting worse It is showing. Second, the increase in average medical revenues in the income statement is small, and the average increase in net profit is small. Thus, medical institutions were able to confirm the difficulty in creating profits through medical activities. In addition, there was a large difference in the debt ratio, the stability ratio, and the profitability ratio of the general hospitals and the general hospitals according to the types of medical institutions, and the difference in the average financial ratios of national and public hospitals, school corporation hospitals, I could confirm. The correlation between independent variables in the correlation was -0.904 between the capital ratio and the total assets turnover ratio, -0.800 between the labor cost ratio and the hospital income ratio, and -0.631 between the labor cost ratio and the foreign profit ratio. In order to improve the management deterioration of hospitals by using accounting information disclosure data of medical institutions, it is necessary to have a large effect on the net profit margin of the medical care and the net profit margin of the total assets.