• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.520-522
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• 2004

분산 감시 제어 시스템은 산업분야에서 중요한 부분이다. 그러나 일반적인 분산 감시 제어 시스템의 응용 소프트웨어간이나 감시 장비간의 또는 응용 소프트웨어와 감시 장비간의 통신이 필요하다. 이러한 문제점은 통신의 과부하로 이어질 수 있다. 본 논문에서는 이러한 문제점을 해결하고 대규모 분산 감시 제어 시스템에서 사용할 수 있는 개발 환경을 제안한다. 이 시스템은 분산 시스템에서 정보를 동기화 하여 분산 환경하의 모든 응용 소프트웨어나 감시 장비가 공유 할 수 있도록 하는 정보 동기화 기술로 이루어져 있다 이 기술은 공유메모리를 사용하여 프로그램 코드와 데이터 구조를 분리하여 데이터 구조 및 데이터 값을 공유할 수 있게 하는 SDSL(Shared Data Structure Library)기법을 사용한다. 그리고 적시성을 보장해 주는 미들웨어인 TMO(Time-triggered Message-triggered Object)를 이용하여 실시간 성을 보장해 주는 한편 통신을 가능하게 해줌으로써 분산 시스템에서도 적용할 수 있다. 본 논문에서 제안하는 개발 환경은 데이터 구조를 동적으로 변화시켜주면서 대규모 분산 감시 제어 시스템에서 응용 프로그램을 보다 편하게 구현하고자 하는 산업 분야에 적용할 수 있다.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.1
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• pp.1-6
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• 1999

This paper is on the analysis for the real-time software requirement. This method can be used for TNPN(Timed Numerical Peri Net) as a easy communication means with real-users. It is based on the RTTL(Real Time Temporal Logic) for correctness the system. TNPN is used to represent a behavior specification language, the validity of specified behaviors in TNPN is expressed in RTTL, and analyzed through the teachability graph. Thus, the requirement between user and system is satisfied Using the example of shared track, the validity of the property of real-time(safetiness, responsiveness, liveness, priority) is verified. Also this framework if given to connection with a object, natually.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.561-564
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• 2009

In this paper, we present an environment configuration of UML CASE tool for internet based collaboration work. We define a method of model sharing in distributed location and construct shared repository. Also we design for model history among work processes and to give responsibility using user authentication. Its result will contribute development of CASE tool supporting collaboration work.

• ETRI Journal
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• v.45 no.1
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• pp.93-104
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• 2023

Coreference resolution is a task in discourse analysis that links several headwords used in any document object. We suggest pointer networks-based coreference resolution for Korean using multi-task learning (MTL) with an attention mechanism for a hierarchical structure. As Korean is a head-final language, the head can easily be found. Our model learns the distribution by referring to the same entity position and utilizes a pointer network to conduct coreference resolution depending on the input headword. As the input is a document, the input sequence is very long. Thus, the core idea is to learn the word- and sentence-level distributions in parallel with MTL, while using a shared representation to address the long sequence problem. The suggested technique is used to generate word representations for Korean based on contextual information using pre-trained language models for Korean. In the same experimental conditions, our model performed roughly 1.8% better on CoNLL F1 than previous research without hierarchical structure.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.78-80
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• 2011

In the area of data fusion, dealing with heterogeneous data sources, numerous models have been proposed in last three decades to facilitate different application domains i.e. Department of Defense (DoD), monitoring of complex machinery, medical diagnosis and smart buildings. All of these models shared the theme of multiple levels processing to get more reliable and accurate information. In this paper, we consider five most widely acceptable fusion models (Intelligence Cycle, Joint Directors of Laboratories, Boyd control, Waterfall, Omnibus) applied to different areas for data fusion. When they are exposed to a real scenario, where large dataset from heterogeneous sources is utilize for object monitoring, then it may leads us to non-efficient and unreliable information for decision making. The proposed variation works better in terms of time and accuracy due to prior data diminution.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.45-52
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• 2004

We propose ESS_WMCE. This paper explains the design and implementation of the EDSS running on ESS_WMCE. EDSS is a synchronization error control system for web based multimedia collaboration environment. We have an error detection approach by using hooking method. The technique of an error transmission is a mended model of utilizing an application sharing system. DOORAE is a good framework model for supporting development on application for computer supported cooperated works. It has primitive service functions. Service functions are implemented with an object oriented concept. It is a system that is suitable for detecting and sharing a software error rapidly occurring on web based multimedia collaboration environment by using software techniques. It is able to share an error as well as providing URL synchronization to access shared objects. When an error occurs, this system detects an error by using hooking methods in MS-Windows API(Application Program Interface) function. If an error is found, it is able to provide an error sharing to access shared objects.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.347-354
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• 2000

This paper presents the efficient mechanisms for concurrency control and writing authority control in collaborative writing system are represented by the tree structures which consist of the logical objects and the content objects connected to the terminal objects of trees. For concurrency control, we adopted the approach to extend the multiple-granularity-locking-scheme. This scheme allows us to lock any objects at each level of the hierarchy. We also defined the locking compatibility table by analysing the operations applicable to any objects at each level of the hierarchy. We finally suggest the extended-multiple-granularity-locking mechanism which uses the locking compatibilility table for deciding to lock an object. This scheme gives the benefit to maximize the possibility of concurrent accessing to the shared objects. In addition, we suggest a mechanism for writing authority control which prohibits the Non-Group users from modifying the shared objects based on the concept of Group/Non-Group The proposed mechanism allows us to protect copyright very reasonably.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.367-373
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• 2022

As deep learning-based autonomous driving technology develops, artificial intelligence models for various purposes have been studied. Based on these studies, several models were used simultaneously to develop autonomous driving systems. It can occur by increasing hardware resource consumption. We propose a multi-tasks model using a shared backbone to solve this problem. This can solve the increase in the number of backbones for using AI models. As a result, in the proposed lightweight model, the model parameters could be reduced by more than 50% compared to the existing model, and the speed could be improved. In addition, each lane can be classified through lane detection using the instance segmentation method. However, further research is needed on the decrease in accuracy compared to the existing model.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.203-219
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• 2011

Previously common users just want to watch the video contents without any specific requirements or purposes. However, in today's life while watching video user attempts to know and discover more about things that appear on the video. Therefore, the requirements for finding multimedia or browsing information of objects that users want, are spreading with the increasing use of multimedia such as videos which are not only available on the internet-capable devices such as computers but also on smart TV and smart phone. In order to meet the users. requirements, labor-intensive annotation of objects in video contents is inevitable. For this reason, many researchers have actively studied about methods of annotating the object that appear on the video. In keyword-based annotation related information of the object that appeared on the video content is immediately added and annotation data including all related information about the object must be individually managed. Users will have to directly input all related information to the object. Consequently, when a user browses for information that related to the object, user can only find and get limited resources that solely exists in annotated data. Also, in order to place annotation for objects user's huge workload is required. To cope with reducing user's workload and to minimize the work involved in annotation, in existing object-based annotation automatic annotation is being attempted using computer vision techniques like object detection, recognition and tracking. By using such computer vision techniques a wide variety of objects that appears on the video content must be all detected and recognized. But until now it is still a problem facing some difficulties which have to deal with automated annotation. To overcome these difficulties, we propose a system which consists of two modules. The first module is the annotation module that enables many annotators to collaboratively annotate the objects in the video content in order to access the semantic data using Linked Data. Annotation data managed by annotation server is represented using ontology so that the information can easily be shared and extended. Since annotation data does not include all the relevant information of the object, existing objects in Linked Data and objects that appear in the video content simply connect with each other to get all the related information of the object. In other words, annotation data which contains only URI and metadata like position, time and size are stored on the annotation sever. So when user needs other related information about the object, all of that information is retrieved from Linked Data through its relevant URI. The second module enables viewers to browse interesting information about the object using annotation data which is collaboratively generated by many users while watching video. With this system, through simple user interaction the query is automatically generated and all the related information is retrieved from Linked Data and finally all the additional information of the object is offered to the user. With this study, in the future of Semantic Web environment our proposed system is expected to establish a better video content service environment by offering users relevant information about the objects that appear on the screen of any internet-capable devices such as PC, smart TV or smart phone.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2213-2220
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• 2017

This paper proposes an efficient approach for hardware implementation of moving object detection (MOD) processor using effective Gaussian mixture learning (EGML)-based background subtraction method. Arithmetic units used in background generation were implemented using LUT-based approximation to reduce hardware complexity. Hardware resources used for both background subtraction and Gaussian probability density calculation were shared. The MOD processor was verified by FPGA-in-the-loop simulation using MATLAB/Simulink. The MOD performance was evaluated by using six types of video defined in IEEE CDW-2014 dataset, which resulted the average of recall value of 0.7700, the average of precision value of 0.7170, and the average of F-measure value of 0.7293. The MOD processor was implemented with 882 slices and block RAM of $146{\times}36kbits$ on Virtex5 FPGA, resulting in 60% hardware reduction compared to conventional design based on EGML. It was estimated that the MOD processor could operate with 75 MHz clock, resulting in real-time processing of $800{\times}600$ video with a frame rate of 39 fps.