• Current Optics and Photonics
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• v.3 no.3
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• pp.220-226
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• 2019

A novel speckle-shifting ghost imaging (SSGI) technique is proposed in this paper. This method can effectively extract the edge of an unknown object without achieving its clear ghost image beforehand. However, owing to the imaging mechanism of SSGI, the imaging result generally contains serious noise. To solve the problem, we further propose a simple and effective method to remove noise from the speckle-shifting ghost image with a connected-region labeling (CRL) algorithm. In this method, two ghost images of an object are first generated according to SSGI. A threshold and the CRL are then used to remove noise from the imaging results in turn. This method can retrieve a high-quality image of an object with fewer measurements. Numerical simulations are carried out to verify the feasibility and effectiveness.

• International Journal of Naval Architecture and Ocean Engineering
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• v.4 no.2
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• pp.123-131
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• 2012

When the object is traveling in the water at tremendously high speeds, the cavity forms and grows up at a fore part of the object called cavitator, and the object is eventually enveloped by vaporized water, supercavitation. As a result, the only part of the object in direct contact with the water is the cavitator, so skin-friction drag is significantly reduced. This is why recently supercavitating objects have been interested in many applicable fields. In this study we are focused out attention on supercavitating flows around various shapes of two and three dimensional cavitators. First, general features of supercavitation are examined by analyzing results obtained by the previously developed numerical method. Second, experimental observations are carried out at a cavitation tunnel at the Chungnam National University (CNU CT), and supercavity dimensions are scrutinized.

• Water for future
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• v.31 no.6
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• pp.21-25
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• 1998

• Journal of Korean Society on Water Environment
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• v.37 no.4
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• pp.275-285
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• 2021

Algal bloom is an important issue in maintaining the safety of the drinking water supply system. Fast detection and classification of algae images are essential for the management of algal blooms. Conventional visual identification using a microscope is a labor-intensive and time-consuming method that often requires several hours to several days in order to obtain analysis results from field water samples. In recent decades, various deep learning algorithms have been developed and widely used in object detection studies. YOLO is a state-of-the-art deep learning algorithm. In this study the third version of the YOLO algorithm, namely, YOLOv3, was used to develop an algae image detection model. YOLOv3 is one of the most representative one-stage object detection algorithms with faster inference time, which is an important benefit of YOLO. A total of 1,114 algae images for 30 genera collected by microscope were used to develop the YOLOv3 algae image detection model. The algae images were divided into four groups with five, 10, 20, and 30 genera for training and testing the model. The mean average precision (mAP) was 81, 70, 52, and 41 for data sets with five, 10, 20, and 30 genera, respectively. The precision was higher than 0.8 for all four image groups. These results show the practical applicability of the deep learning algorithm, YOLOv3, for algae image detection.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.204-206
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• 2003

In order to utilize remote sensed images effectively, a lot of image classification methods are suggested for many years. But, the accuracy of traditional methods based on pixel-based classification is not high in general. In this study, object oriented classification based on image segmentation is used to classify Landsat images. A necessary prerequisite for object oriented image classification is successful image segmentation. Object oriented image classification, which is based on fuzzy logic, allows the integration of a broad spectrum of different object features, such as spectral values , shape and texture. Landsat images are divided into urban, agriculture, forest, grassland, wetland, barren and water in sochon-gun, Chungcheongnam-do using object oriented classification algorithms in this paper. Preliminary results will help to perform an automatic image classification in the future.

• Ocean Systems Engineering
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• v.10 no.4
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• pp.435-449
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• 2020

This paper proposes a method to estimate the underwater target object's yaw angle using a sonar image. A simulator modeling imaging mechanism of a sonar sensor and a generative adversarial network for style transfer generates realistic template images of the target object by predicting shapes according to the viewing angles. Then, the target object's yaw angle can be estimated by comparing the template images and a shape taken in real sonar images. We verified the proposed method by conducting water tank experiments. The proposed method was also applied to AUV in field experiments. The proposed method, which provides bearing information between underwater objects and the sonar sensor, can be applied to algorithms such as underwater localization or multi-view-based underwater object recognition.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.71-76
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• 1998

Water management objects was developed using the Object Oriented Programming (OOP) concept and Irrigation Block Simulation Model was developed using these objects. This model using OOP can simulate the behavior of the irrigation block composed of several irrigation canals, drainage canals, paddy fields, check gates, and so on. This study showed that using OOP concept, we can develop an water management application or extend the function of existing application more easily.

• Journal of the Korean Solar Energy Society
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• v.27 no.4
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• pp.27-33
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• 2007

In this research, to develop the practical application system of fresh water generation system with plate-type fresh water generator using low pressure evaporation method is the main object, and to do that, this study used the evacuated solar collector with operating range of about $50-85^{\circ}C$ as thermal energy source and solar photovoltaic as electric energy source. To achieve that object, this study set up the demo-plant, then estimated and analyzed the usefulness, the safety, and the reliability through pre-tests during short time ahead of the long-time operation. This study showed that the pumps, which are including sea water supply, ejector, hot water supply, and fresh water pumps, were operated one after another. And, the fresh water yield was closely related with the solar irradiance and lower supply temperature of hot water was revealed more reasonable for the solar energy desalination system. That is due to the insufficient area than the solar collector area being required that was estimated through the performance tests of the fresh water generator.

• The Journal of Korea Robotics Society
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• v.7 no.2
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• pp.142-149
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• 2012

The camera has limitations of poor visibility in underwater environment due to the limited light source and medium noise of the environment. However, its usefulness in close range has been proved in many studies, especially for navigation. Thus, in this paper, vision-based object detection and tracking techniques using artificial objects for underwater robots have been studied. We employed template matching and mean shift algorithms for the object detection and tracking methods. Also, we propose the weighted correlation coefficient of adaptive threshold -based and color-region-aided approaches to enhance the object detection performance in various illumination conditions. The color information is incorporated into the template matched area and the features of the template are used to robustly calculate correlation coefficients. And the objects are recognized using multi-template matching approach. Finally, the water basin experiments have been conducted to demonstrate the performance of the proposed techniques using an underwater robot platform yShark made by KORDI.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.5
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• pp.552-567
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• 2017

The floating crane vessel in waves gives rise to the motion of the lifted object which is connected to the hoisting wire. The dynamic tension induced by the lifted object also affects the motion responses of the floating crane vessel in return. In this study, coupled motion responses of a floating crane vessel and a lifted subsea manifold during deep-water installation operations were investigated by both experiments and numerical calculations. A series of model tests for the deep-water lifting operation were performed at Ocean Engineering Basin of KRISO. For the model test, the vessel with a crane control system and a typical subsea manifold were examined. To validate the experimental results, a frequency-domain motion analysis method is applied. The coupled motion equations of the crane vessel and the lifted object are solved in the frequency domain with an additional linear stiffness matrix due to the hoisting wire. The hydrodynamic coefficients of the lifted object, which is a significant factor to affect the coupled dynamics, are estimated based on the perforation value of the structure and the CFD results. The discussions were made on three main points. First, the motion characteristics of the lifted object as well as the crane vessel were studied by comparing the calculation results. Second, the dynamic tension of the hoisting wire were evaluated under the various wave conditions. Final discussion was made on the effect of passive heave compensator on the motion and tension responses.