• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.33-41
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• 2015

Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.

• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.565-572
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• 2011

A modified iterative N-FINDR algorithm is developed for fully automatic extraction of endmembers from hyperspectral image data. This algorithm exploits the advantages of iterative NFINDR technique and Iterative Error analysis technique. The experiments using a simulated hyperspectral image data shows that the optimum number of endmembers can be automatically decided. The extracted endmembers and finally generated abundance fraction maps show the potentialities of the proposed algorithm. More studies are needed for verification of the applicability of the algorithm to the real hyperspectral image data where the absence of pure pixels is common.

• Journal of Navigation and Port Research
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• v.32 no.6
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• pp.447-452
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• 2008

In this paper, the automatic depth control system and the collision avoidance system of the Manta UUV have been established in vertical and horizontal plane. The PID control theory and the Fuzzy theory are adopted in this system. The 6-DOF MMG model had been established by theoretical calculations and captive model test results. The depth control simulation results have been fully presented. The collision risks of the UUV had calculated by the fuzzy theory with the virtual sonar system. Finally, the automatic depth control system and the collision avoidance simulation system of Manta UUV have been fully developed and simulated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.6
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• pp.490-496
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• 2014

The thickness of knee joint cartilage causes most diseases of knee. Therefore, an articular cartilage segmentation of knee magnetic resonance imaging (MRI) is required to diagnose a knee diagnosis correctly. In particular, fully automatic segmentation method of knee joint cartilage enables an effective diagnosis of knee disease. In this paper, we analyze a well-known level-set based segmentation method in brain MRI, and apply that method to knee MRI with solving some problems from different image characteristics. The proposed method, a fully automatic segmentation in whole process, enables to process faster than previous semi-automatic segmentation methods. Also it can make a three-dimension visualization which provides a specialist with an assistance for the diagnosis of knee disease. In addition, the proposed method provides more accurate results than the existing methods of articular cartilage segmentation in knee MRI through experiments.

• The KIPS Transactions:PartA
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• v.10A no.6
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• pp.685-690
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• 2003

The application for PDA as a new wireless Internet device is variously developed to improve the function of PDA, and the application software must be installed to PDAs. In addition. when the power supply of PDA becomes fully discharged, all data stored in the RAM (Random Access Memory) could be vanished, and then the application programs should be reinstalled. This paper presents an automatic installation system of application program, PAIS (PDA Automatic Installation System). It is designed to solve the problem of PDA that PDA's users have to install the application programs on their PDA themselves. When this engine is applied, PDA users can save the time and effort for installation. It's convenient for the PDA users. The PDA and application software company can save the cost to create materials to explain the installation process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.544-547
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• 2002

According to the rising of national economic level. domestic consumption of vegetables having high additive values is increased continuously due to increased consumption of meat in last decade. These vegetables are produced almost in this country and are limited to import from neighbor countries in due of high transportation expenses for storing in refrigerated container. It is very important to mechanize the harvest work, forming more than 30% for their production cost, in order to cultivate variable vegetables at the same time according to their harvesting seasons. In this state its former harvest methods, with using of human power or semi-automatic harvest, caused to increase their production cost due to high labor cost and low working efficiency. The former onion harvest being operated almost by semi-automatic plant distributer mechanism have many limit and troublesome for cultivation spaces, vinyle mulched ridge, gravel mixture in soil. Therefore, it is necessary to develope a fully automatic and self-running situation and overcome above handicaps, even in the farm covered with vinyle house or mulch sheets. This newly developed onion harvest can be applied to plant various young trees and will be able to export together with onion haying their competition in the worldwide market in which the culinary vegetable method or farm conditions is similar to our country.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4248-4270
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• 2018

This research aims at a new practical Intent fuzzing tool for detecting Intent vulnerabilities of Android apps causing the robustness problem. We proposed two new ideas. First, we designed an Intent specification language to describe the structure of Intent, which makes our Intent fuzz testing tool flexible. Second, we proposed an automatic tally method classifying unique failures. With the two ideas, we implemented an Intent fuzz testing tool called Hwacha, and evaluated it with 50 commercial Android apps. Our tool offers an arbitrary combination of automatic and manual Intent generators with executors such as ADB and JUnit due to the use of the Intent specification language. The automatic tally method excluded almost 80% of duplicate failures in our experiment, reducing efforts of testers very much in review of failures. The tool uncovered more than 400 unique failures including what is unknown so far. We also measured execution time for Intent fuzz testing, which has been rarely reported before. Our tool is practical because the whole procedure of fuzz testing is fully automatic and the tool is applicable to the large number of Android apps with no human intervention.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.346-349
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• 2018

In North-East asian countries, laver cultivation has been an important marine industry in coastal areas as well as fishery because laver (Porphyra) is nutrient-rich food and has been used in many Asian cuisines. Laver is characterized by high concentrations of fiber and minerals, a low fat content, and, in some cases, relatively high protein levels. In this paper we inplimented design of fully automatic laver harvesting, nowdays most peoples are used to collect a laver harvesting by human, it is very defficult working, due to wind, waves, and the weather conditions which is hard to stand on the ship and holding the seaweed nets it can be injurced human, this is the reason to we are developed automatic harvesting method, in this project we proposed automatic harvesting collect method which is operated without human. Mainly we design and developed automated ship, This ship is devided in to three parts frist part is supporting roller, second part is drum screener, thried part is lifting mechanism. Thise are operated with hydro pnumatic equimpment, this divice are control with micro controller. The system prototype has implemented and satisfied by the performance to realize the further level.

• PNF and Movement
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• v.22 no.1
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• pp.1-11
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• 2024

Purpose: The prevalent use of mobile devices may contribute to musculoskeletal disorders, such as forward head posture (FHP), among users. The measurement of the craniovertebral angle (CVA) using photographic images is frequently employed in assessing FHP. Although manual CVA measurement using photographic images is reliable in clinical settings, computer programs or mobile applications to support tele-physical therapy are not yet fully developed. Therefore, in the current study, we propose an automatic method for extracting CVA from photographic images of FHP subjects to facilitate tele-physical therapy. Methods: To develop the automatic CVA measuring computer program, photographic images were obtained from 10 FHP participants. The location information obtained from the markers attached to the tragus and the spinous process of the seventh cervical vertebra were used as coordinates. Using these coordinates, straight line 1 was generated by connecting the seventh spinous process of the cervical vertebra and the tragus, while straight line 2 was drawn parallel to the coordinate obtained from the seventh spinous process of the cervical vertebra. The arc tangent function was used to calculate the angle between the two straight lines. The automatic CVA measurement computer program utilizing photographic images was developed using MATLAB (ver. 2016b). Results: The results showed that the automatic CVA measurement computer program demonstrated stable repeatability and high accuracy. Conclusion: The proposed approach was able to automatically estimate the CVA using photographic images. The developed computer program can potentially be used for easier and more reliable clinical assessment of FHP.

• International Journal of Contents
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• v.14 no.1
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• pp.1-6
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• 2018

Text, as one of the most influential inventions of humanity, has played an important role in human life since ancient times. The rich and precise information embodied in text is very useful in a wide range of vision-based applications such as the text data extracted from images that can provide information for automatic annotation, indexing, language translation, and the assistance systems for impaired persons. Therefore, natural-scene text detection with active research topics regarding computer vision and document analysis is very important. Previous methods have poor performances due to numerous false-positive and true-negative regions. In this paper, a fully-convolutional-network (FCN)-based method that uses supervised architecture is used to localize textual regions. The model was trained directly using images wherein pixel values were used as inputs and binary ground truth was used as label. The method was evaluated using ICDAR-2013 dataset and proved to be comparable to other feature-based methods. It could expedite research on text detection using deep-learning based approach in the future.