• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.381-390
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• 2007

3D object contents are used for various applications in the Web virtual space, where the main concerns are to navigate the 3D virtual space and visualize 3D objects. The techniques to manipulate 3D objects like disassembling and assembling and to record the manipulation process are the very first step. Until now, we can record only the result of 3D object manipulation. Thus, we have tried to study the representation technique to record meaningfully and replay the manipulation process of 3D structured objects. We analyzed the structures and their relations between components to construct 3D objects that are described in XML or VRML. Compared to the previous method, we studied a XML based annotation technique to record and store selectively by user. This technique makes 3D structured objects be used in the various applications by the selective recording and also selective replaying.

• Journal of KIISE
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• v.45 no.3
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• pp.224-233
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• 2018

Recently, there are many of studies on SWRL reasoning engine based on user-defined rules in a distributed environment using a large-scale ontology. Unlike the schema based axiom rules, efficient inference orders cannot be defined in SWRL rules. There is also a large volumet of network shuffled data produced by unnecessary iterative processes. To solve these problems, in this study, we propose a method that uses Map-Reduce algorithm and distributed in-memory framework to deduce multiple rules simultaneously and minimizes the volume data shuffling occurring between distributed machines in the cluster. For the experiment, we use WiseKB ontology composed of 200 million triples and 36 user-defined rules. We found that the proposed reasoner makes inferences in 16 minutes and is 2.7 times faster than previous reasoning systems that used LUBM benchmark dataset.

• Journal of KIISE:Software and Applications
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• v.28 no.10
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• pp.773-784
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• 2001

Since documents on the Web are naturally partitioned into may document database, the efficient information retrieval process requires identifying the document database that are most likely to provide relevant documents to the query and then querying the identified document database. We propose a neural net agent approach to such an efficient information retrieval. First, we present a neural net agent that learns about underlying document database using the relevance feedbacks obtained from many retrieval experiences. For a given query, the neural net agent, which is sufficiently trained on the basis of the BPN learning mechanism, discovers the document database associated with the relevant documents and retrieves those documents effectively. In the experiment, we introduce a neural net agent based information retrieval system and evaluate its performance by comparing experimental results to those of the conventional well-known approaches.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.5
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• pp.9-14
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• 2014

Recently, various contents using human motion are developed in computer vision and game industries. If we try to apply human motion to application programs and contents, users can experience a sense of immersion getting into it so that the users feel a high level of satisfaction from the contents. In this research, we analyze human head motion using images captured from an webcam and then we apply the result of motion recognition to a game without special devices as an interface. The proposed method, first, segments human head region using an image composed of MHI(Motion History Image) and the result of skin color detection, and then we calculate the direction and distance by the MHI sequence. In experiments, the proposed method for human head motion recognition was tested for controlling a game player. From the experimental results we proved that the proposed method can make a gammer feel more immersed into the game. Furthermore, we expect the proposed method can be an interface of a serious game for medical or rehabilitation purposes.

• Membrane Journal
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• v.16 no.1
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• pp.1-8
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• 2006

Nanofiber is a broad phrase generally referring to a fiber with diameter less than 1 micron. Various polymers have been successfully electrospun into nanofibers in recent years. These nanofibers, due to their high surface area and porosity, have a great potential for use as filter medium, adsorption layers in protective clothing, etc. Nanofiber filters will enable new levels of filtration performance in the field of air filtration. In particular, nanofibers provide marked increases in filtration efficiency at relatively small pressure drop in permeability. Therefore, nanofiber filters could be substituted for conventional filter market due to the easy application of process and the possibility of coating to micron-sized non-woven sheets. This review is discussed on the trend of researche and development related to nanofiber filter including future marketability.

• The Journal of Korean Institute of Information Technology
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• v.17 no.7
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• pp.31-45
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• 2019

The core technologies for intelligent services today are deep learning, that is neural networks, and parallel and distributed processing technologies such as GPU parallel computing and big data. However, for intelligent services and knowledge sharing services through globally shared ontologies in the future, there is a technology that is better than the neural networks for representing and reasoning knowledge. It is a knowledge representation of IF-THEN in RIF or SWRL, which is the standard rule language of the Semantic Web, and can be inferred efficiently using the rete algorithm. However, when the number of rules processed by the rete algorithm running on a single computer is 100,000, its performance becomes very poor with several tens of minutes, and there is an obvious limitation. Therefore, in this paper, we analyze the past and current studies on parallel and distributed processing of rete algorithm, and examine what aspects should be considered to implement an efficient rete algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.44-49
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• 2021

Recently, due to COVID-19, studies have been popularly worked to apply neural network to mask wearing automatic detection system. For applying neural networks, the 1-stage detection or 2-stage detection methods are used, and if data are not sufficiently collected, the pretrained neural network models are studied by applying fine-tuning techniques. In this paper, the system is consisted of 2-stage detection method that contain MTCNN model for face recognition and ResNet model for mask detection. The mask detector was experimented by applying five ResNet models to improve accuracy and fps in various environments. Training data used 17,217 images that collected using web crawler, and for inference, we used 1,913 images and two one-minute videos respectively. The experiment showed a high accuracy of 96.39% for images and 92.98% for video, and the speed of inference for video was 10.78fps.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.37-45
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• 2022

As of 2020, about 500 hours of videos are uploaded to YouTube, a representative online video platform, per minute. As the number of users acquiring information through various uploaded videos is increasing, online video platforms are making efforts to provide better recommendation services. The currently used recommendation service recommends videos to users based on the user's viewing history, which is not a good way to recommend videos that deal with specific purposes and interests, such as educational videos. The recent recommendation system utilizes not only the user's viewing history but also the content features of the item. In this paper, we extract the content features of educational video for educational video recommendation based on YouTube, design a recommendation system using it, and implement it as a web application. By examining the satisfaction of users, recommendataion performance and convenience performance are shown as 85.36% and 87.80%.

• Journal of IKEEE
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• v.27 no.4
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• pp.610-616
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• 2023

In this paper, we implement an unmanned delivery robot system with Robot Operating System(ROS)-based mobile manipulator, and introduce the technologies employed for the system implementation. The robot consists of a mobile robot capable of autonomous navigation inside the building using an elevator and a Selective Compliance Assembly Robot Arm(SCARA)-Type manipulator equipped with a vacuum pump. The robot can determines the position and orientation for picking up a package through image segmentation and corner detection using the camera on the manipulator. The proposed system has a user interface implemented to check the delivery status and determine the real-time location of the robot through a web server linked to the application and ROS, and recognizes the shipment and address at the delivery station through You Only Look Once(YOLO) and Optical Character Recognition(OCR). The effectiveness of the system is validated through delivery experiments conducted within a 4-story building.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.23-26
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• 2023

In the past, in observing the sea fog on the major sea route and providing real-time information for the safe operation of ships, a visibility sensor or a fog detector with similar operating principles was installed to observe local fog near the place where it was installed. However, it was somewhat unreasonable to immediately provide sea fog observation information to ships and users because the reliability of real-time observation information was somewhat low due to pollution caused by dust, salt, and pollen, or malfunctions of detection sensors by organisms such as spider webs. From 2019 to 2022, the Korea Meteorological Administration and the Ministry of Oceans and Fisheries collaborated to build a more reliable real-time image-based sea fog observation system in 100 regions of the Lighthouse on major sea routes across the country to collect reliable sea fog observation information every 10 minutes and perform real-time public service(webpage).