• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.59-77
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• 2007

Advances in mobile techknowledges and supporting techniques require an effective representation and analysis of moving objects. Similarity search of moving object trajectories is an active research area in data mining. In this paper, we propose a trajectory search algorithm for spatio-temporal similarity of moving objects on road network. For this, we define spatio-temporal distance between two trajectories of moving objects on road networks, and propose a new method to measure spatio-temporal similarity based on the real road network distance. In addition, we propose a similar trajectory search algorithm that retrieves spatio-temporal similar trajectories in the road network. The algorithm uses a signature file in order to retrieve candidate trajectories efficiently. Finally, we provide performance analysis to show the efficiency of the proposed algorithm.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.3
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• pp.808-817
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• 2016

This study aims at reviewing differences of awareness toward speech-language therapy according to background variables of child-care teachers, and establishing a basic data necessary for special education support programs afterwards based on child-care centers and its characteristics with the results. Researcher carried out a survey by objecting child-care teachers of Chungcheongbuk-do, Korea, and looked into existence of some differences through SPSS 20.0 for Window, independent sample t-Test, ANOVA, Scheffe post verification on background characteristics such as level of education, working career, license grade, whether or not to have objects of speech-language objects in the class. Research results are same as follows. First, significant differences in awareness of child-care teachers toward speech-language therapy appeared from license grade among characteristics like level of education, license grade, whether or not to have objects of speech-language therapy in the class. Second, significant differences were displayed from whether or not to have objects of speech-language therapy in the class among characteristics such as level of education, working career, license grade, and whether or not to have objects of speech-language therapy. When putting these results together, a conclusion could be made such like awareness of child-care teachers toward speech-language therapy and therapists is able to be different a little according to background variables of teachers.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.420-432
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• 2014

In detection of moving objects from video sequences, an essential process for intelligent visual surveillance, the cast shadows accompanying moving objects are different from background so that they may be easily extracted as foreground object blobs, which causes errors in localization, segmentation, tracking and classification of objects. Most of the previous research results about moving cast shadow detection and removal usually utilize color information about objects and scenes. In this paper, we proposes a novel cast shadow removal method of moving objects in gray level video data for visual surveillance application. The proposed method utilizes observations about edge patterns in the shadow region in the current frame and the corresponding region in the background scene, and applies Laplacian edge detector to the blob regions in the current frame and the corresponding regions in the background scene. Then, the product of the outcomes of application determines moving object blob pixels from the blob pixels in the foreground mask. The minimal rectangle regions containing all blob pixles classified as moving object pixels are extracted. The proposed method is simple but turns out practically very effective for Adative Gaussian Mixture Model-based object detection of intelligent visual surveillance applications, which is verified through experiments.

• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.229-235
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• 2017

In recent years, research has been actively carried out to recognize and recognize objects based on a large amount of data. In this paper, we propose a system that extracts objects that are thought to be obstacles in road driving images and recognizes them by car, man, and motorcycle. The objects were extracted using Optical Flow in consideration of the direction and size of the moving objects. The extracted objects were recognized using Alexnet, one of CNN (Convolutional Neural Network) recognition models. For the experiment, various images on the road were collected and experimented with black box. The result of the experiment showed that the object extraction accuracy was 92% and the object recognition accuracy was 96%.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.331-341
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• 2002

In order to extract 3-dimensional information from 2-D image, stereo images are prerequisite. Moreover, for the measurement of moving objects, the synchronized sequential stereo images have to be captured and image matching should be implemented for determining the location of moving objects. In this research, a simple method computing 3-dimensional coordinates from sequential images of moving objects was implemented. The sequential stereo images were captured by a video camera with a beam splitter. Once video images were digitalized by frame grabber, the interest points were extracted and matched in each stereo image, and the coordinates of center of them are calculated using weighted average method. Then, 3-dimensional coordinates of moving objects were computed by DLT algorithms.

• Ocean Systems Engineering
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• v.10 no.4
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• pp.415-434
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• 2020

Detecting objects is important for the safe operation of ships, and enables collision avoidance, risk detection, and autonomous sailing. This study proposes a ship detection method from images and videos taken at sea using one of the state-of-the-art deep neural network-based object detection algorithms. A deep learning model is trained using a public maritime dataset, and results show it can detect all types of floating objects and classify them into ten specific classes that include a ship, speedboat, and buoy. The proposed deep learning model is compared to a universal trained model that detects and classifies objects into general classes, such as a person, dog, car, and boat, and results show that the proposed model outperforms the other in the detection of maritime objects. Different deep neural network structures are then compared to obtain the best detection performance. The proposed model also shows a real-time detection speed of approximately 30 frames per second. Hence, it is expected that the proposed model can be used to detect maritime objects and reduce risks while at sea.

• Culinary science and hospitality research
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• v.12 no.1 s.28
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• pp.126-143
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• 2006

The purpose of this study is to analyze menu-related research. The findings are as follows. First, menu-related studies have concentrated on menu engineering, menu management, menu development. Therefore, researchers must be diversified the field of researches. Second, methodology of menu-related studies has concentrated on survey research and literature research. Therefore, experiment research and case study must be done. Third, the objects of menu-related research have centered on hotels and family restaurants, so researchers should study diverse objects. Finally, techniques of statistics must be applied in various ways.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.367-370
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• 2004

We model a moving object as a sizable physical entity equipped with GPS, wireless communication capability, and a computer such as a PDA and mobile phone. Furthermore, we have observed that a real trajectory of a moving object is the result of interactions among moving objects in the system yielding Multi-points instead of a line segment. In this paper, the new types and operations are integrated seamlessly into the moving object framework to achieve a relatively simple, consistent and powerful overall model and query language for constrained and unconstrained movement.

• Journal of Korea Game Society
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• v.12 no.5
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• pp.43-56
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• 2012

The purpose of this research is to provide the rationality of placement of game objects using the space analysis for game map so that the game designers can find out the proper position for each object in the map. The significance of this research is beyond the limitations of the existing research using Space Syntax theory is confined to the analysis of the behavior of players in the map, this research suggest the method of the efficient placement of game objects in level design step. This paper as the worth of the industry is expected to be able to reduce the repetitive tasks that may occur during game level design steps. Through this, it is also expected by reducing game development period and development costs in accordance with the reasonable placement of game objects.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.53-60
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• 2017

The purpose of this study is to provide empirical and quantitative analysis on user's perceived privacy, security, and user satisfaction when providing visualization information about objects and service provider behaviors that users can not perceive in internet service process. Through previous research, we have examined the importance of privacy and security factors as a key factor to be considered for the characteristics of the Internet of things and the Internet of things. In addition, service blueprint, which is one of the service design methodologies to examine the flow of service usage in providing Internet service of things, was examined. In the flow of things internet service utilization, it is found that the things that are out of the user's cognitive area and the behavior of the service provider take up a large part. Therefore, the hypothesis that the trust of the Internet service security and the satisfaction of the user experience can be improved by providing the security visualization information about the behavior of the object and the invisible service provider in the non-contact aspect of the user and the object. In order to verify the hypothesis, we conducted experiments and questionnaires on the use of virtual objects' internet environment and conducted statistical analysis based on them. As a result, it was analyzed that visual information feedback on non - contact and invisible objects and service provider's behaviors had a positive effect on user's perceived privacy, security, and satisfaction. In addition, we conclude that it can be used as a service design evaluation tool to eliminate psychological anxiety about security and to improve satisfaction in internet service design. We hope that this research will be a great help for the research on application method of service design method in Internet environment of objects.