• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.6
• /
• pp.97-103
• /
• 2017

For high quality of software, it should be necessary for defining and analyzing the exact requirements at the early stage of software development. But readability and understandability of most natural language requirements are inaccurate and difficult for identifying use cases. The requirements are duplicated for objects or temrs with the same meaning. To solve this problem, it should need an effective way of requirement analysis based on linguistic and semantic textual analysis. In this paper, we propose to improve a semantic analysis method adopted with a linguist Fillmore's linguistic mechanism. This method may expect to analyze easily readable and exactly understandable requirements specifications through modeling the goal oriented use cases with natural language based requirements.

• Proceedings of the Korea Contents Association Conference
• /
• 2005.11a
• /
• pp.48-52
• /
• 2005

R&D Personnel information is constructed locally based on the needs of each institute and therefore is distributed over different databases. It does not support inter operability which makes it difficult to access and update that leads to the problem of ineffective usage. In this study, we have categorized the lower level information that forms the domestic S&T Personnel and defined the relationship between each type of information to suggest a standard for the data elements that guarantee the access to specific information in order to support inter operability. We have analyzed the human resource information database of domestic and foreign research institutes for the data modeling. We have also made reference to the standard metadata and database of other types that can be linked with the human resource information in designing the data elements. ISO/IEC 11179, the international standard for the metadata registry(MDR), was adopted to apply the object, attribute and expression to be described to the name of the data element.

• Journal of Digital Contents Society
• /
• v.6 no.2
• /
• pp.107-112
• /
• 2005

We need a research for representing and processing of multimedia data in database because of increasing the importance and utilization of the data owing to development of internet technology. RDBMS supports only the storing-structure to store multimedia, but the support for data type, representation and query of multimedia is insufficient. To cope with this problem, ISO/IEC standardized SQL multimedia(SQL/MM) for multimedia data. However, ORDBMS supports SQL/MM, but RDBMS does not support it. Therfore, this theis proposes a query interpreter to support SQL/MM in MS-SQL 2000 as one of RDBMS and introduces a image retrieval application using it. The quary interpreter supports the function to convert SQL/MM into SQL, and additionally the function of the image duplication check. The image processing application using a query interpreter can easily be integrated and operated with traditional RDBMS-based system.

• The Journal of the Korea Contents Association
• /
• v.18 no.2
• /
• pp.147-157
• /
• 2018

Recently, with the advancement of network technologies, and the activation of IoT and social network services, many graph stream data have been generated. As the relationship between objects in the graph streams changes dynamically, studies have been conducting to detect or analyze the change of the graph. In this paper, we propose a scheme to incrementally detect frequent patterns by using frequent patterns information detected in previous sliding windows. The proposed scheme calculates values that represent whether the frequent patterns detected in previous sliding windows will be frequent in how many future silding windows. By using the values, the proposed scheme reduces the overall amount of computation by performing only necessary calculations in the next sliding window. In addition, only the patterns that are connected between the patterns are recognized as one pattern, so that only the more significant patterns are detected. We conduct various performance evaluations in order to show the superiority of the proposed scheme. The proposed scheme is faster than existing similar scheme when the number of duplicated data is large.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.6
• /
• pp.124-136
• /
• 2019

Autonomous driving at intersections requires assistance by exchanging traffic information between traffic objects due to the intersection of various vehicles and complicated driving environment. For this reason, traffic information exchange between adjacent intersections is required, but the node ID representing the intersection in the Korean standard node link system have limitations in updating intersections and identifying location information of intersections through IDs due to the configuration system including serial numbers. In this paper, we designed a coordinate-based intersection ID configuration system created by processing and merging two-dimensional coordinates of intersections to include location information in the intersection ID. In order to verify the applicability of the proposed intersection ID, we applied a new intersection ID to domestic intersections and confirmed that there are no duplicate values. Coordinate-based intersection ID reduces data size by 60% compared to existing node ID, and enables spatial queries such as searching for nearby intersections and extracting intersections in specific areas in the form of boxes without GIS tools. Therefore, coordinate-based intersection ID is expected to be more scalable and utilized than existing node ID.

• Journal of Korea Spatial Information System Society
• /
• v.8 no.1 s.16
• /
• pp.37-57
• /
• 2006

To support Location Based Services, the technology to store and search locations information of moving objects effectively was needed. And the study about indexes to manage these moving objects effectively has been done. As these indexes for moving objects was not considered for the objects which are moving along constrained networks such as road and railroad, indexes for the moving objects based on constrained networks was proposed. But these kinds of indexes have two problems as following. First, as the indexes for the moving objects based on constrained networks is divided according to time domain, when the places of moving objects from the present to the past are needed, the problem to search past indexes as well as present indexes occurs. Second, in this case, we should construct both present indexes and past indexes, so we have no other choice but to spend space cost and reconstruction cost additionally. This paper proposes A Unified Index for Moving Objects in Constrained Networks to solve these kinds of problems. As this proposed indexes support both present location and past location of moving objects, it can solve the current problems such as when we search present and past location of moving objects, we need a separate processing procedure. And as it consolidated the common parts of current location indexes and past location indexes, we can use less space cost and reconstruction cost than when we maintain indexes separately.

• Journal of Korea Water Resources Association
• /
• v.46 no.4
• /
• pp.345-359
• /
• 2013

In order to manage water quality efficiently and systematically through TMDL (Total Maximum Daily Load), the demand for the construction of spatial data for stream networks has increased for use with GIS-based water quality modeling, data management and spatial analysis. The objective of this study was to present an improved KRF (Korean Reach File) design as framework data for domestic stream networks to be used for various purposes in relation to the TMDL. In order to achieve this goal, the US EPA's RF (River Reach File) was initially reviewed. The improved design of the graphic and attribute data for the KRF based on the design of the EPA's RF was presented. To verify the results, the KRF was created for the Han River Basin. In total, 2,047 stream reaches were divided and the relevant nodes were generated at 2,048 points in the study area. The unique identifiers for each spatial object were input into the KRF without redundancy. This approach can serve as a means of linking the KRF with related database. Also, the enhanced topological information was included as attributes of the KRF. Therefore, the KRF can be used in conjunction with various types of network analysis. The utilization of KRF for water quality modeling, data management and spatial analysis as they pertain to the applicability of the TMDL should be conducted.

• Journal of KIISE:Databases
• /
• v.28 no.3
• /
• pp.512-527
• /
• 2001

In a client-server spatial database, it is desirable to maintain the cached data in a client side to minimize the communication overhead across a network. This paper deals with the issues of concurrency and consistency of map updates in this environment. A client transaction to update map data is an interactive work and takes a long time to complete it. The map update in a client site may affect the other sites'updates because of dependencies between spatial data stored at different sites. The concurrent updates should be propagated to the other clients as well as the server to keep the consistency of map replicated in a client cache, and also the communication overhead of the update propagation should be minimized not to lose the benefit of caching. The newly proposed cache region locking with CR lock and CX lock controls the update dependency due to spatial relationships. CS lock and COD lock are suggested to use optimistic detection-based approaches for guaranteeing the consistency of cached client data. The cooperative update protocol uses these extended locking primitives and Spatial Relationship-based 2PC (SR-based 2PC). This paper argues that the concurrent updates of cached client spatial data can be achieved by deciding on collaborative updates or independent updates based on spatial relationships.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.3
• /
• pp.199-206
• /
• 2023

This study utilizes deep learning algorithms to automatically classify construction waste into three categories: wood waste, plastic waste, and concrete waste. Two models, VGG-16 and ViT (Vision Transformer), which are convolutional neural network image classification algorithms and NLP-based models that sequence images, respectively, were compared for their performance in classifying construction waste. Image data for construction waste was collected by crawling images from search engines worldwide, and 3,000 images, with 1,000 images for each category, were obtained by excluding images that were difficult to distinguish with the naked eye or that were duplicated and would interfere with the experiment. In addition, to improve the accuracy of the models, data augmentation was performed during training with a total of 30,000 images. Despite the unstructured nature of the collected image data, the experimental results showed that VGG-16 achieved an accuracy of 91.5%, and ViT achieved an accuracy of 92.7%. This seems to suggest the possibility of practical application in actual construction waste data management work. If object detection techniques or semantic segmentation techniques are utilized based on this study, more precise classification will be possible even within a single image, resulting in more accurate waste classification

• Korean Journal of Remote Sensing
• /
• v.39 no.2
• /
• pp.193-205
• /
• 2023

A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.