• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1542-1552
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• 1996

This paper presents a design and implementation of an extended directory system in manage and provide an effective search operation of the DFR(Document Filing and Retrieval) Object's attributes. For this, the design and implementation of a configuration model for interworking between the DFR and directory systems, an association mechanisms between two application's operation, extended directory schema and extended DIT(Directory Information Tree) are described. In a distributed environment, the interworking between the DFR and directory system implemented by using QUIPU 8.0 of ISODE(ISO Development Environment) directory system is tested. based on the result of this paper, an extended model of the directory system is proposed for proving search operation of various application's objects.

• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.85-92
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• 2018

This study aimed to reduce of traps incident of metro train door by suggesting preventive actions throughout analyzing why railway drivers and passengers commit unsafe behaviors which are human factors making occurrence of the incidents. The incident cases were analyzed and Incident Tree was structured by brainstorming with safety experts. In addition, the questionnaire survey was conducted for comparison with the analysis results. As the result, this study suggested driver's factors, passenger's factors, and public relation plan for safe use of metro in order to reduce the frequency of the incidents. For driver's factors, implementing job-rotation systems between railway and non-railway drivers, installing Object Detection Sensors between the metro doors and PSD, and flexible operation of dwell time were suggested. For passenger's factors, placing a platform safety person, installing a safety fence in front of the stairs and the elevators, and country wide public relations through mass media were suggested.

• Journal of the Society of Naval Architects of Korea
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• v.39 no.3
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• pp.75-80
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• 2002

In these days of severe struggle for existence, the world has changed a great deal to global and digital oriented period. The enterprises try to introduce new management and production system to adapt such a change. But, if the only new technologies are applied to an enterprise without definite analysis about manufacturing, failure fellows as a logical consequence. Hence, enterprise must analyze manufacturing system definitely and needs new methodologies to mitigate risk. This study suggests that the new approach, which is systems approach for process improvement, is organized to systems analysis, systems diagnosis, and systems verification. Systems analysis analyzes manufacturing systems with object-oriented methodology-UML(Unified Modeling language) from a point of product, process, and resource view. Systems diagnosis identifies the constraints to optimize the system through scientific management or TOC(Theory of constraints). Systems verification shows the solution with virtual manufacturing technique applied to the core problem which emerged from systems diagnosis. This research shows the artifacts to improve the productivity with the above methodology applied to forming shop. UML provides the definite tool for analysis and re-usability to adapt itself to environment easily. The logical tree of TOC represents logical tool to optimize the forming shop. Discrete event simulator-QUEST suggests the tool for making a decision to verify the optimized forming shop.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.21-26
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• 2009

A sensor system capable of automatically recognize activities would allow many potential Ubiquitous applications. This paper presents a new system for recognizing the activities of daily living(ADL) like walking, running, standing, sitting, lying etc. The system based on the state-dependent motion analysis using Tri-Accelerometer and Zigbee tag. Two accelerometers are used for the classification of body and hand activities. Classification of the environment and instrumental activities is performed based on the hand interaction with an object ID using.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.279-286
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• 2000

The objective of this research is to detect the papaya fruits on tree in an orchard. The detection of papaya on natural background is difficult because colors of fruits and background such as leaves are similarly green. We cannot separate it from leaves by color information. Therefore, this research will use shape information instead. First, we detect an interested object by detecting its boundary using edge detection technique. However, the edge detection will detect every objects boundary in the image. Therefore, shape description technique will be used to describe which one is the interested object boundary. The good shape description should be invariant in scaling, rotating, and translating. The successful concept is to use Fourier series, which is called "Fourier Descriptors". Elliptic Fourier Descriptors can completely represent any shape, which is selected to describe the shape of papaya. From the edge detection image, it takes a long time to match every boundary directly. The pre-processing task will reduce non-papaya edge to speed up matching time. The deformable template is used to optimize the matching. Then, clustering the similar shapes by the distance between each centroid, papaya can be completely detected from the background.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.6
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• pp.635-642
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• 2000

In this paper, we proposed an efficient document conversion mechanism to provide a adaptive web document to mobile terminals. We also proposed a RHTML(Reduced HTML) to archive the adaptive tag reduction. Markup error correction process in the proposed adaptive document conversion mechanism converts a HTML(HyperText Markup Language) document into a XML(Extensible Markup Language) application document. This. process makes web document easy to handle with a DOM (Document Object Mode)) as the tree model and removes the hardware overhead in mobile terminals. Also, tag reduction process provides the adaptive web document with three DTD(Document Type Definition)s in the RHTML.

• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.240-245
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• 2016

In this study, comments on restaurants, movies, and mobile devices, as well as tweet messages regardless of specific domains were analyzed for sentimental information content. We proposed a system for extraction of objects (or aspects) and opinion words from each sentence and the subsequent evaluation. For the sentiment analysis, we conducted a comparative evaluation between the Structural SVM algorithm and the Latent Structural SVM. As a result, the latter showed better performance and was able to extract objects/aspects and opinion words using VP/NP analyzed by the dependency parser tree. Lastly, we also developed and evaluated the sentiment detector model for use in practical services.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.320-324
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• 2023

As urbanization accelerates and facilities that use energy increase, human life and property damage due to fire is increasing. Therefore, a fire monitoring system capable of quickly detecting a fire is required to reduce economic loss and human damage caused by a fire. In this study, we aim to develop an improved artificial intelligence model that can increase the accuracy of low fire alarms by mixing DeepSORT, which has strengths in object tracking, with the YOLOv5s model. In order to develop a fire detection model that is faster and more accurate than the existing artificial intelligence model, DeepSORT, a technology that complements and extends SORT as one of the most widely used frameworks for object tracking and YOLOv5s model, was selected and a mixed model was used and compared with the YOLOv5s model. As the final research result of this paper, the accuracy of YOLOv5s model was 96.3% and the number of frames per second was 30, and the YOLOv5s_DeepSORT mixed model was 0.9% higher in accuracy than YOLOv5s with an accuracy of 97.2% and number of frames per second: 30.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.967-970
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• 2020

In a previous work we have done, we presented a monitoring system to automatically detect some dogs' behaviors from videos. However, the input video data used by that system was pre-trimmed to ensure it contained a dog only. In a real-life situation, the monitoring system would continuously receive video data, including frames that are empty and ones that contain people. In this paper, we propose a YOLOv4-based system for automatic object detection and trimming of dog videos. Sequences of frames trimmed from the video data received from the camera are analyzed to detect dogs and people frame by frame using a YOLOv4 model, and then records of the occurrences of dogs and people are generated. The records of each sequence are then analyzed through a rule-based decision tree to classify the sequence, forward it if it contains a dog only or ignore it otherwise. The results of the experiments on long untrimmed videos show that our proposed method manages an excellent detection performance reaching 0.97 in average of precision, recall and f-1 score at a detection rate of approximately 30 fps, guaranteeing with that real-time processing.

• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.194-207
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• 2003

This paper presents an optimal design methodology for the multidimensional nested attribute index (MD-NAI) that uses a multidimensional index structure for indexing the nested attributes in object databases. The MD-NAI efficiently supports complex queries involving both nested attributes and class hierarchies, which are not supported by the nested attribute index using one-dimensional index structure such as $B^+$-tree. However, the performance of the MD-NAI is very degraded in some cases of user's query types. In this paper, for the performance enhancement of the MD-NAI, we first determine the optimal shape of index page region by using the query information about the nested predicates, and then construct an optimal MD NAI by applying a region splitting strategy that makes the shape of the page regions of the MD-NAI as close as possible to the predetermined optimal one. For performance evaluation, we perform extensive experiments with the MD-NAI using various types of nested predicates and object distribution. The results indicate that our proposed method builds optimal MD-NAI regardless of the query types and object distributions. When the interval ratio of a three-dimensional query region is 1:16:236, the performance of the proposed method is enhanced by as much as 5.5 times over that of the conventional method employing the cyclic splitting strategy.