• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2162-2166
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• 2016

This paper describes the implementation of AUSV system for sonar image acquisition to survey the seabed. The system is controlled by Feed Forward PID algorithm on the vessel for bearing of the thrusters composed of motion sensor and DGPS which calculates the differences between the current location and the destination location for longitude and latitude based on GPS coordinates. As experimental results, the bearing control performance is good that the error distance from the destination positions are under 6m in total survey track of 1km. And the sonar image deviation of a object is under 12 pixels from the manned survey method, which the comparison with the total image quality is almost the same as the manned survey one. Thus the proposed AUSV system is a new method of system can be utilized at the limited survey areas as the surveyor should not be able to approach on sea surface by onboard vessel.

• Journal of KIISE:Databases
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• v.30 no.4
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• pp.397-407
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• 2003

Transactions of updating spatial dta with mobile clients are log transactions because a user disconnected from a server surveys real features and updates them. In this environment, it is appropriate to exploit the optimistic approach based on the validation test in order to control the concurrency of transactions. On the contrary, the pessimistic concurrency control scheme makes transactions wait for a long time due to the lock. In this paper, we propose the surrogate transaction model and implement its manager for the S-S-M(Server-Surrogate PC-Mobile Client) structure which is appropriate for updating spatial data in mobile environments. In the S-S-M structure, the mobile client communicates with the server by the surrogate PC. We extend the validation condition in consideration of spatial relationships between spatial objects in this model. We also present the commit protocol where the user of a surrogate PC adjusts objects of the conflicted surrogate transaction to minimize costs for the abortion of the transaction.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.2
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• pp.89-94
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• 2016

This paper proposed a facial expression recognition approach using SIFT feature and SVM classifier. The SIFT was generally employed as feature descriptor at key-points in object recognition fields. However, this paper applied the SIFT descriptor as feature vector for facial expression recognition. In this paper, the facial feature was extracted by applying SIFT descriptor at each sub-block image without key-point detection procedure, and the facial expression recognition was performed using SVM classifier. The performance evaluation was carried out through comparison with binary pattern feature-based approaches such as LBP and LDP, and the CK facial expression database and the JAFFE facial expression database were used in the experiments. From the experimental results, the proposed method using SIFT descriptor showed performance improvements of 6.06% and 3.87% compared to previous approaches for CK database and JAFFE database, respectively.

• Journal of Intelligence and Information Systems
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• v.12 no.4
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• pp.91-107
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• 2006

This study introduces a software system for supporting the engineering process of container terminals. The design procedure consists of data input, capacity requirements, alternative design, alternative evaluation, and results output. In order to design and evaluate alternatives rapidly, a set of libraries for container terminals was developed. The libraries consist of Wharf, Yard, TravellingArea, and Gate. The architecture of the set of libraries was designed by an object-oriented approach. Various types of container terminal models can be constructed by using a user friendly interface, the CAD based environment, and the combinations of the elements of the libraries. Alternative models can be evaluated by a simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.271-274
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• 2006

This paper deals with a similarity decision method between the shape of hand-postures and their structures to improve performance of the vision-based hand-posture recognition system. Hand-posture recognition by vision sensors has difficulties since the human hand is an object with high degrees of freedom, and hence grabbed images present complex self-occlusion effects and, even for one hand-posture, various appearances according to viewing directions. Therefore many approaches limit the relative angle between cameras and hands or use multiple cameras. The former approach, however, restricts user's operation area. The latter requires additional considerations on the way of merging the results from each camera image to get the final recognition result. To recognize hand-postures, we use both of appearance and structural features and decide the similarity between the two types of features by learning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.401-406
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• 2008

Fall event detection is one of the most common problems for elderly people, especially those living alone because falls result in serious injuries such as joint dislocations, fractures, severe head injuries or even death. In order to prevent falls or fall-related injuries, several previous methods based on video sensor showed low fall detection rates in recent years. To improve this problem and outperform the system performance, this paper presented a novel approach for fall event detection in the elderly using a subtraction between successive difference images and temporal templates in real time environment. The proposed algorithm obtained the successful detection rate of 96.43% and the low false positive rate of 3.125% even though the low-quality video sequences are obtained by a USB PC camera sensor. The experimental results have shown very promising performance in terms of high detection rate and low false positive rate.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.577-586
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• 2022

Detection and classification of steel surface defects are critical for product quality control in the steel industry. However, due to its low accuracy and slow speed, the traditional approach cannot be effectively used in a production line. The current, widely used algorithm (based on deep learning) has an accuracy problem, and there are still rooms for development. This paper proposes a method of steel surface defect detection combining EfficientNetV2 for image classification and YOLOv5 as an object detector. Shorter training time and high accuracy are advantages of this model. Firstly, the image input into EfficientNetV2 model classifies defect classes and predicts probability of having defects. If the probability of having a defect is less than 0.25, the algorithm directly recognizes that the sample has no defects. Otherwise, the samples are further input into YOLOv5 to accomplish the defect detection process on the metal surface. Experiments show that proposed model has good performance on the NEU dataset with an accuracy of 98.3%. Simultaneously, the average training speed is shorter than other models.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.101-109
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• 2009

An encryption module is equipped basically at 8i version ideal of Oracle DBMS, encryption module, but a performance decrease is caused, and users are restrictive. We analyze problem of DB security by technology by circles at this paper whether or not there is an index search, object management disorder, a serious DB performance decrease by encryption, real-time data encryption beauty whether or not there is data approach control beauty circular-based IP. And presentation does the comprehensive security Frame Work which utilized the DB Masking technique that is an alternative means technical encryption in order to improve availability of DB security. We use a virtual account, and set up a DB Masking basis by security grades as alternatives, we check advance user authentication and SQL inquiry approvals and integrity after the fact through virtual accounts, utilize to method as collect by an auditing log that an officer was able to do safely DB.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.206-212
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• 2022

This study suggests art makeup design by utilizing the characteristics of psychedelic works. The study analyzed the concept of being psychedelic and art makeup based on precedent studies and publications, and classified the psychedelic characteristics as being those of mysterious, optical illusions, and playfulness. After selecting the work featuring the characteristics of being psychedelic, six works were created with this motif, by integrating the airbrush, the pictorial, and the object techniques of the art makeup expression techniques. As a result, it was demonstrated that the design that has utilized the characteristics of psychedelic works could be applicable to art makeup. Next, the confluence of art works and art makeup can serve as an approach to drawing creative designs. Thus, this study suggests a direction for extending the creativity and variety of art makeup design, and a continued development for art makeup design by further confluences with various areas is expected

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.11-16
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• 2023

The technology of 3D reconstruction, primarily relying on point cloud data, is essential for digitizing objects or spaces. This paper aims to utilize reinforcement learning to achieve the acquisition of point clouds in a given environment. To accomplish this, a simulation environment is constructed using Unity, and reinforcement learning is implemented using the Unity package known as ML-Agents. The process of point cloud acquisition involves initially setting a goal and calculating a traversable path around the goal. The traversal path is segmented at regular intervals, with rewards assigned at each step. To prevent the agent from deviating from the path, rewards are increased. Additionally, rewards are granted each time the agent fixates on the goal during traversal, facilitating the learning of optimal points for point cloud acquisition at each traversal step. Experimental results demonstrate that despite the variability in traversal paths, the approach enables the acquisition of relatively accurate point clouds.