• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1426-1433
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• 2000

As distributed computing systems become popular, many modeling techniques and methods have been developed in specify the specification formally and verify the distributed/concurrent sytems. In spite of importance of communication in distributed object-oriented systems, specifying of communication method generally has not been emphasized in the design phase. One reason is due to the system designer misunderstanding, that is, a specification needs to be independent on the implementation. However, since defining communication pattern indistributed object-oriented systems is more serious than the required message passing method in the design phase. specifying the communication pattern is necessary instead of postponing until the implementation. In this paper, two formal specification techniques, temporal logic method and Petri nets method, for the communication in distributed systems are discussed. One is based on the temporal logic, which specifies the different patterns of primitive predicates. This method enable to define the underlying mechanism which can be interpreted as constraints. The Petri net method helps to specify the dynamic behavior of communicational patterns using the properties of Petri nets.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.313-314
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• 2007

In this paper, we suggest robust object extraction algorithm taking advantage of efficient Belief Propagation method. It does not get a disparity information because of uniform region and occlusion region etc. on initial depth map that use forward direction disparity information although is object area. Therefore, We run parallel backward disparity information and brightness information for certain object extraction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1546-1549
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• 2020

This paper introduces the development process of mobile home CCTV that enables remote control and object recognition using unused smartphones and Arduino. Clients can control motors connected to Arduino through button, enable bidirectional voice communication between client-server and receive video from the server in real time. The server sends a PUSH notification to the client when its battery is low. When the server recognizes the charger, the client's remote control allows the server to dock to the charger and charge it. It was confirmed that video and voice delivery between client and server works well without any problems, and that object recognition works smoothly.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.267-270
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• 2005

An RFID patch antenna for metallic object has been designed. The effects of variation of distance between the tag antenna and ground of the antenna have been studied. Various dielectric constants, thickness, permittivity, width of transmission line and length of transmission line have been used to design the better tag antenna for metallic object.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.156-165
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• 2021

In this paper, we propose an histogram weighted centroid based Siamese region proposal network for object tracking. The original Siamese region proposal network uses two identical artificial neural networks which take two different images as the inputs and decide whether the same object exist in both input images based on a similarity measure. However, as the Siamese network is pre-trained offline, it experiences many difficulties in the adaptation to various online environments. Therefore, in this paper we propose to incorporate the histogram weighted centroid feature into the Siamese network method to enhance the accuracy of the object tracking. The proposed method uses both the histogram information and the weighted centroid location of the top 10 color regions to decide which of the proposed region should become the next predicted object region.

• Journal of the Korean Society of Costume
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• v.52 no.8
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• pp.41-54
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• 2002

This study discusses the beauty of the ideal body shown by fashion communication media, and explains how aesthetic aspects of, the body are being expressed in contemporary fashion. The beauty of the body may be considered as the beauty of sexual, controllable or consumable object. First. the most vigorously discussed point about the body is its sexual aspect, the most outstanding of which is the voluptuous and the androgynous beauty in contemporary fashion. Second, the body is an object which has been oppressed or controlled under the name of history. morality. and rationality. The things making us regard the body itself as an aesthetic object may be considered as dynamic and functional beauty Third, the sexual instinct and the body are fetishized as consumer goods, and women's bodies are presented as comsumer objects whose most parts could be restored to exchangeable value. The consumable beauty presented in contemporary fashion is the conspicuous beauty and the decadent beauty. So far, the various aspects of the beautiful body has been considered, based on the beauty of the ideal body shown by the fashion communication media. Man exists through on his body. but it is the embodied and formed body that serves as a means to manifest his social status and cultural ties. A natural body is reformed as a cultural phenomenon in various artificial ways. Popular culture has transmitted a series of new body image by creating and reproducing symbols and images, and has made the ideal body. Now there is not only one standard for the ideal beauty in our society. The standard of the beauty has changed continuously. There has been an aesthetic sense which can represent the times during the process of those changes. The various communication media have played a role of mirror reflecting those changes. The ideal body in contemporary times is no more an abstract media to express classical beauty, but an object directly affecting us, who are living in the crisis of subjectivity and identity.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.6
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• pp.771-781
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• 1999

오늘날의 컴퓨팅 환경은 통신 네트워크의 복잡성과 다양한 멀티미디어 서비스 처리를 위해 객체지향 기술을 분산 시스템에 도입하고 통신망을 소프트웨어 계층적 모델로 구조화한 개방형 정보 통신망 구조 연구가 활발히 진행되고 있다. 본 논문은 분산환경에서 멀티미디어 스트림 데이타를 전송하기 위한 아키텍쳐에 관한 모델의 설계 및 구현에 관한 것으로 분산 환경에서 멀티미디어 스트림 데이타를 효율적으로 전송할 수 있는 구조를 제시하고 있다. 설계한 구조는 Point-to-Point와 멀티캐스트를 지원하며 컴퓨터 통신망에서 멀티캐스트 연결을 효율적으로 관리하고 추후 기능 확장 및 기능 변경이 용이하도록 모듈화하고 유연성을 가지는 연결 관리 구조를 설계하고 구현하였다. 신호기능은 CORBA(Common Object Request Broker Architecture)의 ORB를 이용하여 실현하였으며, 데이타 전송 기능은 TCP/IP연결을 이용하였다. 이렇게 신호처리 부분과 데이타 전송 부분을 독립적으로 만들어서 하부망 기술에 독립적인 연결 관리 구조를 채택하고 있으므로 향후 다른 환경에서도 신호처리 부분을 그대로 적용할 수 있다. 분산 객체 개념을 적용하여 연결 관리 기능을 분산 객체화 하였으며 각 분산 객체간 인터페이스를 OMG(Object Management Group) IDL(Interface Definition Language)로 정의함으로써 유연성을 갖도록 하였다.AbstractThis paper proposes communication service architecture to support dynamic communication configuration and multiple connection management which are required to handle a variety of multimedia multicast application. Our communication service architecture was designed to fulfil the objectives as the following:- To build a common networking system for various multimedia multicast services- To build a platform for rapid service development and provisioning- To provide service networking independent on transport network technologiesWe implemented communication service architecture based on Common Object Request Broker Architecture (CORBA) for multimedia multicast applications. Our communication service architecture is distributed and object-oriented for extensibility and easy modification. The interfaces between the distributed objects are specified in (Object Management Group) OMGs Interface Definition Language.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.204-211
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• 2020

In this paper, we propose an optimal deep learning network architecture for main object location detection through weak supervised learning. The proposed network adds convolution blocks for improving the localization accuracy of the main object through weakly-supervised learning. The additional deep learning network consists of five additional blocks that add a composite product layer based on VGG-16. And the proposed network was trained by the method of weakly-supervised learning that does not require real location information for objects. In addition, Grad-CAM to compensate for the weakness of GAP in CAM, which is one of weak supervised learning methods, was used. The proposed network was tested through the CUB-200-2011 data set, we could obtain 50.13% in top-1 localization error. Also, the proposed network shows higher accuracy in detecting the main object than the existing method.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.12
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• pp.301-312
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• 2018

In industrial wireless sensor networks, the continuous object detection such as fire or toxic gas detection is one of major applications. A continuous object occurs at a specific point and then diffuses over a wide area. Therefore, many studies have focused on accurately detecting a continuous object and delivering data to a static sink with an energy-efficient way. Recently, some applications such as fire suppression require mobile sinks to provide real-time response. However, the sink mobility support in continuous object detection brings challenging issues. The existing approaches supporting sink mobility are designed for individual object detection, so they establish one-to-one communication between a source and a mobile sink for location update. But these approaches are not appropriate for a continuous object detection since a mobile sink should establish one-to-many communication with all sources. The one-to-many communication increases energy consumption and thus shortens the network lifetime. In this paper, we propose the origin-centric communication scheme to support sink mobility in a continuous object detection. Simulation results verify that the proposed scheme surpasses all the other work in terms of energy consumption.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.76-85
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• 2019

We introduce a vision-based object detection method for real-time video surveillance system in low-end edge computing environments. Recently, the accuracy of object detection has been improved due to the performance of approaches based on deep learning algorithm such as Region Convolutional Neural Network(R-CNN) which has two stage for inferencing. On the other hand, one stage detection algorithms such as single-shot detection (SSD) and you only look once (YOLO) have been developed at the expense of some accuracy and can be used for real-time systems. However, high-performance hardware such as General-Purpose computing on Graphics Processing Unit(GPGPU) is required to still achieve excellent object detection performance and speed. To address hardware requirement that is burdensome to low-end edge computing environments, We propose sub-frame analysis method for the object detection. In specific, We divide a whole image frame into smaller ones then inference them on Convolutional Neural Network (CNN) based image detection network, which is much faster than conventional network designed forfull frame image. We reduced its computationalrequirementsignificantly without losing throughput and object detection accuracy with the proposed method.