• Journal of Internet Computing and Services
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• v.3 no.1
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• pp.81-90
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• 2002

Large-scale distributed applications based on Internet and client/server applications have to deal with series of problems. Load balancing, unpredictable communication delays, and networking failures can be the example of the series of problems. Therefore. sophisticated applications such as teleconferencing, video-on-demand, and concurrent software engineering require an abstracted group communication, CORBA does not address these paradigms adequately. It mainly deals with point-to-point communication and does not support the development of reliable applications that include predictable behavior in distributed systems. In this paper, we present our design, implementation and performance analysis of the group communication using the CORBA-ORB. JAVA-RML and Socket based on distributed computing Performance analysis will be estimated latency-lime according to object increment, in case of group communication using ORB of CORBA the average is 14.5172msec, in case of group communication using RMI of Java the average is 21.4085msec, in case of group communication using socket the average is becoming 18.0714msec. Each group communication using multicast and UDP can be estimated 0.2735msec and 0.2157msec. The performance of the CORBA-ORB group communication is increased because of the increased object by the result of this research. This study can be applied to the fault-tolerant client/server system, group-ware. text retrieval system, and financial information systems.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.137-143
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• 2014

Recently, as new paradigm for government operation called government 3.0, government is actively operating policy opening and sharing public data. In addition, the Ministry of Land are operating an open platform integrated map service (the VWorld) which provides a variety of video contents such as the country's national spatial information, traffic information and three-dimensional building for the public. According to W3C Foundation's Open Data Status Report(2013), our country has the evaluated results that the part of the government's policy support and planning is good while the part of the data management is vulnerable. So our country needs the quality improvement for the data management. In addition, a digital aerial photograph image data is required to be up-to-date for the three-dimensional spatial object data. In this paper, we present the method for enhancement of the accuracy of vertical position and for maintainment of up-to-date vertical position. Our methods evaluate the data quality and analyze the cause of error of measurement utilizing the national standard quality assessment method. The result of research shows that the accuracy of vertical position is improved if the height of the building captain is adjusted by the quality assessment values and a three-dimensional model has up-to-date data if reconstruction and extension information of construction register is utilized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.165-167
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• 2022

The proportion of cat cats among companion animals has been increasing at an average annual rate of 25.4% since 2012. Cats have strong wildness compared to dogs, so they have a characteristic of hiding diseases well. Therefore, when the guardian finds out that the cat has a disease, the disease may have already worsened. Symptoms such as anorexia (eating avoidance), vomiting, diarrhea, polydipsia, and polyuria in cats are some of the symptoms that appear in cat diseases such as diabetes, hyperthyroidism, renal failure, and panleukopenia. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia (drinking a lot of water), polyuria (a large amount of urine), and frequent urination (urinating frequently) more quickly. In this paper, 1) Efficient version of DeepLabCut for posture prediction running on an artificial intelligence server, 2) yolov4 for object detection, and 3) LSTM are used for behavior prediction. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the main server system.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.44-55
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• 2022

In order to automatically provide information on fruits in agricultural related broadcasting contents, instance image segmentation of target fruits is required. In addition, the information on the 3D pose of the corresponding fruit may be meaningfully used. This paper represents research that provides information about tomatoes in video content. A large amount of data is required to learn the instance segmentation, but it is difficult to obtain sufficient training data. Therefore, the training data is generated through a data augmentation technique based on a small amount of real images. Compared to the result using only the real images, it is shown that the detection performance is improved as a result of learning through the synthesized image created by separating the foreground and background. As a result of learning augmented images using images created using conventional image pre-processing techniques, it was shown that higher performance was obtained than synthetic images in which foreground and background were separated. To estimate the pose from the result of object detection, a point cloud was obtained using an RGB-D camera. Then, cylinder fitting based on least square minimization is performed, and the tomato pose is estimated through the axial direction of the cylinder. We show that the results of detection, instance image segmentation, and cylinder fitting of a target object effectively through various experiments.

• Cartoon and Animation Studies
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• s.50
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• pp.43-73
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• 2018

This is a study on 'Objet' in animation culture art education. Research on the use of Objet in modern art is actively under way. From Cubism to Dadaism, Surrealism, Futurism and Pop art, it is no exaggeration to say that the Objet is stepping with modern art. In addition, Objet has a remarkable value in the field of visual arts expressing 'motion' such as kinetic art, video art, media art, and animation. However, there are not many cases of classifying and studying the types of Objets used in artworks. Therefore, this researcher has been influenced by the surrealism discourse and prepared six types of Objets type analysis framework. And the research focused on 'the aesthetic emotion and educational aspect of creativity improvement' of Objet animation was conducted. The type analysis framework is named as a drawing Objet, Objet of existence, a morphine Objet, epidermis Objet, assigned Objet and assemblage Objet and this type is presented and analyzed with case image. The data used in this study was focused on the outcome of Objet animation that were trained for non-experts in culture and arts education. This aesthetic emotion refers to Freud's desire for life (Eros) as Attraction, and desire for death (Thanatos) as Uncanny (fearful unfamiliarity) and explains the conflicting concept with the Animism, the indigenous religion. Next, educational aspects of Objet animation creativity improvement in relation to the term 'functional fixedness' was discussed as described by Gestalt psychologist Karl Duncker (1903-1940). Overcoming the functional fixedness is a phenomenon that is fixed only to the functional aspects of things and can't be changed. In this study, the educational aspect of creativity improvement was demonstrated as a case of overcoming the functional fixedness through 'Objet Animation' culture and art education. Ultimately, this study is to prove the aesthetic emotion and creativity of the Objet animation by analyzing Objet types. Furthermore, it is meaningful to suggest direction when using 'Objet Animation' in culture and arts education.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.297-309
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• 2023

The degradation of coastal ecosystems and fishery environments is accelerating due to the recent phenomenon of invertebrate grazers. To effectively monitor and implement preventive measures for this phenomenon, the adoption of remote sensing-based monitoring technology for extensive maritime areas is imperative. In this study, we compared and analyzed the robustness of deep learning-based object detection modelsfor detecting and monitoring invertebrate grazersfrom underwater videos. We constructed an image dataset targeting seven representative species of invertebrate grazers in the coastal waters of South Korea and trained deep learning-based object detection models, You Only Look Once (YOLO)v7 and YOLOv8, using this dataset. We evaluated the detection performance and speed of a total of six YOLO models (YOLOv7, YOLOv7x, YOLOv8s, YOLOv8m, YOLOv8l, YOLOv8x) and conducted robustness evaluations considering various image distortions that may occur during underwater filming. The evaluation results showed that the YOLOv8 models demonstrated higher detection speed (approximately 71 to 141 FPS [frame per second]) compared to the number of parameters. In terms of detection performance, the YOLOv8 models (mean average precision [mAP] 0.848 to 0.882) exhibited better performance than the YOLOv7 models (mAP 0.847 to 0.850). Regarding model robustness, it was observed that the YOLOv7 models were more robust to shape distortions, while the YOLOv8 models were relatively more robust to color distortions. Therefore, considering that shape distortions occur less frequently in underwater video recordings while color distortions are more frequent in coastal areas, it can be concluded that utilizing YOLOv8 models is a valid choice for invertebrate grazer detection and monitoring in coastal waters.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.2
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• pp.295-307
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• 1998

This article is an overview of the digital library project, indicating what roles Koreas diverse digital collections may play. Our digital library prototype has simple architecture, consisting of digital repositories, filters, indexing and searching, and clients. Digital repositories include various types of materials and databases. The role of filters is to recognize a format of a document collection and mark the structural components of each of its documents. We are using a database management system (ORACLE and ConText) supporting user-defined functions and access methods that allows us to easily incorporate new object analysis, structuring, and indexing technology into a repository. Clients can be considered browsers or viewers designed for different document data types, such as image, audio, video, SGML, PDF, and KORMARC. The combination of navigational tools supports a variety of approaches to identifying collections and browsing or searching for individual items. The search interface was implemented using HTML forms and the World Wide Web's CGI mechanism.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.169-181
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• 1997

In this paper, we propose and discuss about image enhancement techniques for MPEG-4. which represents very low bit-rate, content-based. and object-based hierarchical audio-visual coding standard. The proposed enhancement technique removes undesired artifacts arising in the compression procedure and increase resolution in both spatial and temporal domains. In order to remove undesired artifacts. we divide the MPEG-4 video algorithm in two parts: MPEG-2 like part and the new part. For removing artifacts caused by the first part. we adopt the conventional blocking artifacts algorithm developed for MPEG-2. On the other hand for removing artifacts caused by the second part. we provide a new degradation model. and propose the corresponding image restoration method. For increasing resolution of the MPEG-4 images, we propose a general framework of multichannel image interpolation process. which includes both spatial and temporal interpolations. As the MPEG-4 standard is under development. various sophisticated techniques are considered. but research on image enhancement techniques is relatively underestimated. By this reason. additional image enhancement techniques will become very important issue in realization phase of MPEG-4.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.252-263
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• 2016

Road sign is an important street furniture that gives some information such as road conditions, driving direction and condition for a driver. Thus, road sign is a major target of image recognition for self-driving car, ADAS(autonomous vehicle and intelligent driver assistance systems), and ITS(intelligent transport systems). In this paper, an enhanced road sign recognition system is proposed for MMS(Mobile Mapping System) using the single camera and GPS. For the proposed system, first, a road sign recognition scheme is proposed. this scheme is composed of detection and classification step. In the detection step, object candidate regions are extracted in image frames using hybrid road sign detection scheme that is based on color and shape features of road signs. And, in the classification step, the area of candidate regions and road sign template are compared. Second, a Geo-marking scheme for geo-content that is consist of road sign image and coordinate value is proposed. If the serious situation such as car accident is happened, this scheme can protect geographical information of road sign against illegal users. By experiments with test video set, in the three parts that are road sign recognition, coordinate value estimation and geo-marking, it is confirmed that proposed schemes can be used for MMS in commercial area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1103-1109
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• 2014

The motion recognition system has been broadly studied in digital image and video processing fields. Recently, method using th depth image is used very useful. However, recognition accuracy of depth image based method will be loss caused by size and shape of object distorted for angle of the depth sensor. Therefore, distortion correction of depth sensor is positively necessary for distinguished performance of the recognition system. In this paper, we propose a pre-processing algorithm to improve the motion recognition system. Depth data from depth sensor converted to real world, performed the corrected angle, and then inverse converted to projective world. The proposed system make progress using the OpenCV and the window program, and we test a system using the Kinect in real time. In addition, designed using Verilog-HDL and verified through the Zynq-7000 FPGA Board of Xilinx.