• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.46 no.4
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• pp.476-486
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• 2010

Fishing efficiency of a trawl vessel can be enhanced by increasing the swept area per unit time, which can be attained either by increasing the mouth size of the net, or by increasing the towing speed. To improve fishing and fuel efficiency of trawl vessels targeting fishes of greater mobility, in which the towing speed is more critical in determining fishing efficiency, we conducted a series of model tests to evaluate the performance of the newly-designed nozzle propeller before installing it in a trawl vessel to verify its towing speed and fuel efficiency in the sea. By conducting further model tests in the experimental basin, we redesigned the propeller of stern trawler to improve the resistance and propulsion performance. Through actual fishing operations, we evaluated the improvement in fuel and fishing efficiency by installing the new nozzle propeller. The trawling speed increased by 0.6kts at the same engine power (RPM), while the engine margin increased by more than 20%. The increased towing speed by installing the redesigned propeller is expected to enhance fishing performance through increasing the number of hauling- and casting operations per unit times, while shortening the towing duration. Analysis of the Catch-Per-Unit-Effort (CPUE) data indicated that the mean CPUE of trawl fishery increased from 3.04kg/m in year 2007 to 6.15kg/m in year 2008, confirming enhanced fishing efficiency by adopting the redesigned propeller.

• Korean Journal of Radiology
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• v.25 no.4
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• pp.363-373
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• 2024

Objective: To develop and evaluate a deep learning model for automated segmentation and detection of bone metastasis on spinal MRI. Materials and Methods: We included whole spine MRI scans of adult patients with bone metastasis: 662 MRI series from 302 patients (63.5 ± 11.5 years; male:female, 151:151) from three study centers obtained between January 2015 and August 2021 for training and internal testing (random split into 536 and 126 series, respectively) and 49 MRI series from 20 patients (65.9 ± 11.5 years; male:female, 11:9) from another center obtained between January 2018 and August 2020 for external testing. Three sagittal MRI sequences, including non-contrast T1-weighted image (T1), contrast-enhanced T1-weighted Dixon fat-only image (FO), and contrast-enhanced fat-suppressed T1-weighted image (CE), were used. Seven models trained using the 2D and 3D U-Nets were developed with different combinations (T1, FO, CE, T1 + FO, T1 + CE, FO + CE, and T1 + FO + CE). The segmentation performance was evaluated using Dice coefficient, pixel-wise recall, and pixel-wise precision. The detection performance was analyzed using per-lesion sensitivity and a free-response receiver operating characteristic curve. The performance of the model was compared with that of five radiologists using the external test set. Results: The 2D U-Net T1 + CE model exhibited superior segmentation performance in the external test compared to the other models, with a Dice coefficient of 0.699 and pixel-wise recall of 0.653. The T1 + CE model achieved per-lesion sensitivities of 0.828 (497/600) and 0.857 (150/175) for metastases in the internal and external tests, respectively. The radiologists demonstrated a mean per-lesion sensitivity of 0.746 and a mean per-lesion positive predictive value of 0.701 in the external test. Conclusion: The deep learning models proposed for automated segmentation and detection of bone metastases on spinal MRI demonstrated high diagnostic performance.

• Computers and Concrete
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• v.14 no.4
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• pp.387-403
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• 2014

The aim of this study is to assess the structural performance of deteriorated reinforced concrete bridge piers, and to provide method for developing improved evaluation method. For a deteriorated bridge piers, once the cover spalls off and bond between the reinforcement and concrete has been lost, compressed reinforcements are likely to buckle. By using a sophisticated nonlinear finite element analysis program, the accuracy and objectivity of the assessment process can be enhanced. A computer program, RCAHEST (Reinforced Concrete Analysis in Higher Evaluation System Technology), is used to analyze reinforced concrete structures. Material nonlinearity is taken into account by comprising tensile, compressive and shear models of cracked concrete and a model of reinforcing steel. Advanced deteriorated material models are developed to predict behaviors of deteriorated reinforced concrete. The proposed numerical method for the structural performance assessment of deteriorated reinforced concrete bridge piers is verified by comparing it with reliable experimental results. Additionally, the studies and discussions presented in this investigation provide an insight into the key behavioral aspects of deteriorated reinforced concrete bridge piers.

• Computers and Concrete
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• v.33 no.4
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• pp.361-372
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• 2024

Reinforced concrete (RC) bridge columns are typically designated as the primary source of energy dissipation for a bridge structure during an earthquake. Therefore, seismic repair of RC bridge columns has been studied extensively during the past several decades. On the other hand, few studies have been conducted to evaluate how repaired column members influence the system-level response of an RC bridge structure in subsequent earthquakes. In this study, a numerical model was established to simulate the response of two large-scale RC columns, repaired using different techniques, reported in the literature. The columns were implemented into a prototype bridge model that was subjected to earthquake loading. Incremental dynamic analysis (IDA) and fragility analysis were conducted on numerical bridge models to evaluate the efficacy of the repairs and the post-repair seismic performance of the prototype bridge that included one or more repaired columns in various locations. For the prototype bridge herein modeled, the results showed that a confinement-enhanced oriented repair would not affect the seismic behavior of the prototype bridge. Increasing the strength of the longitudinal reinforcement could effectively reduce the drift of the prototype bridge in subsequent earthquakes. A full repair configuration for the columns was the most effective method for enhancing the seismic performance of the prototype bridge. To obtain a positive effect on seismic performance, a minimum of two repaired columns was required.

• Journal of KIISE:Software and Applications
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• v.33 no.1
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• pp.95-104
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• 2006

The Gradient Vector Flow (GVF) snake or active contour model offers the best performance for image segmentation. However, there are problems in classical snake models such as the limited capture range and the slow progress into concavity. This paper presents a new method for enhancing the performance of the GVF snake model by extending the external force fields from the neighboring fields and using a modified smoothing method to regularize them. The results on a simulated U-shaped image showed that the proposed method has larger capture range and makes it possible for the contour to progress into concavity more quickly compared with the conventional GVF snake model.

• Journal of computational fluids engineering
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• v.22 no.1
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• pp.103-109
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• 2017

The aerodynamic noise reduction of railway traction motor is required to satisfy new enhanced Korean noise regulations for a train. This paper is the study result on a noise reduction of a railway traction motor using Lattice Boltzmann Method(LBM). To verify the reliability of numerical analysis, the noise performance of the base model evaluated using LBM, and calculated result was compared with the experimental data. In addition, main noise sources were selected to design parameters through analyzing the flow field of the base model. Based on the noise sources analysis result, a design improvement model of traction motor for this study was derived to reduce the noise. The performance of a design improvement model was evaluated by applying a validated numerical scheme. As a result, it was confirmed that the noise was reduced due to the suppression of the internal turbulent flow components.

• Steel and Composite Structures
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• v.50 no.5
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• pp.549-562
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• 2024

In this study a steel moment frame system to be installed on the exterior surface of an existing structure is proposed as a seismic retrofit device. The seismic performance of the retrofit system was investigated by installing it on the exterior of a single story single bay reinforced concrete frame and testing it under cyclic loading. The cyclic loading test results indicated that the steel frame significantly enhanced the strength and ductility of the bare structure. Finite element analysis was carried out to validate the test results, and it was observed that there was good agreement between the two results. An analytical model was developed in order to apply the retrofit system to an example structure subjected to seven mainshock-aftershock sequential earthquake records. It was observed that the model structure was severely damaged due to the mainshock earthquakes, and the seismic response of the model structure increased significantly due to the subsequent aftershock earthquakes. The seismic retrofit of the model structure using the proposed steel frame turned out to be effective in decreasing the seismic response below the given limit state.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.327-330
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• 2008

It is required that a server which communicates with various client simultaneously should have an efficient data transfer model. In Windows$^{(R)}$ environment, the server was generally developed based on IOCP model. Developing the IOCP model, the server generally has one data transfer buffer per client. If the server divides a larger data than the transfer buffer into several fragments, there used to be a problem in sending it to a client, because there is a conflict in a data transfer buffer. That is, CPU requests one data-fragment transfer, then it will request the next data-fragment transfer successively before completing the previous request, owing to the property of overlapped IO model. In this paper, we proposed the transfer buffer sharing technique to solve the conflicting problem. The experimental result shows that the performance of data transfer was enhanced by 39% maximally.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.99-101
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• 2006

Auto-Cross Correlated time series (ACTS) model was constructed by using the backpropagation neural network. The performance of ACTS model was evaluated with sensor information collected from a large volume, industrial plasma-enhanced chemical vapor deposition system. A total of 18 sensor information were collected. The effect of inclusion of past and future information were examined. For all but three sensor information with a large data variance demonstrated a prediction error less than 3%. By integrating ACTS model into equipment software, process quality can be more stringently monitored while improving device throughput.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.102-104
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• 2006

Auto-Correlated time series (ATS) model was constructed by using the backpropagation neural network. The performance of ATS model was evaluated with sensor information collected from a large volume, industrial plasma-enhanced chemical vapor deposition system. A total of 18 sensor information were collected. The effect of inclusion of past and future information were examined. For all but three sensor information with a large data variance demonstrated a prediction error less than 4%. By integrating ATS model into equipment software, process quality can be more stringently monitored while improving device throughput.