• Journal of KIISE:Software and Applications
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• v.35 no.7
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• pp.431-441
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• 2008

The academic information analysis service is including automatic recommendation of reviewers and analysis of researchers' accomplishments. The service of recommendation of reviewers should be processed in a transparent, fair and accountable way. When selecting reviewers, the following information must be considered: subject of project, reviewer's maj or, expertness of reviewer, relationship between applicant and reviewer. The analysis service of researchers' accomplishments is providing statistic information of researcher, institution and location based on accomplishments including book, article, patent, report and work of art. In order to support these services, we designed ontology for academic information, converted legacy data to RDF triples, expanded knowledge appropriate to services using OntoFrame. OntoFrame is service framework which includes ontology, reasoning engine, triple store. In our study, we propose the design methodology of ontology and service system for academic information based on OntoFrame. And then we explain the components of service system, processing steps of automatic recommendation of reviewers and analysis of researchers' accomplishments.

• Smart Media Journal
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• v.5 no.4
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• pp.26-40
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• 2016

Recent researches have been conducted for a user of the position acquisition and analysis since the mobile devices was developed. Trajectory data mining of location analysis method for a user is used to extract the meaningful information based on the user's trajectory. It should be preceded by a process of extracting Stay Point. In order to carry out trajectory data mining by analyzing the user of the GPS Trajectory. The conventional Stay Point extraction algorithm is low confidence because the user to arbitrarily set the threshold values. It does not distinguish between staying indoors and outdoors. Thus, the ambiguity of the position is increased. In this paper we proposed extraction method of Stay Point using a statistical analysis. We proposed algorithm improves position accuracy by extracting the points that are staying indoors and outdoors using Gaussian distribution. And we also improve reliability of the algorithm since that does not use arbitrarily set threshold.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_1
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• pp.507-516
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• 2007

Segmentation and organization of the LiDAR (Light Detection and Ranging) data of the Earth's surface are difficult tasks because the captured LiDAR data are composed of irregularly distributed point clouds with lack of semantic information. The reason for this difficulty in processing LiDAR data is that the data provide huge amount of the spatial coordinates without topological and/or relational information among the points. This study introduces LiDAR data segmentation technique by utilizing histograms of the LiDAR height image data and analyzing roof shape for 3D reconstruction and visualization of the buildings. One of the advantages in utilizing LiDAR height image data is no registration required because the LiDAR data are geo-referenced and ortho-projected data. In consequence, measurements on the image provide absolute reference coordinates. The LiDAR image allows measurement of the initial building boundaries to estimate locations of the side walls and to form the planar surfaces which represent approximate building footprints. LiDAR points close to each side wall were grouped together then the least-square planar surface fitting with the segmented point clouds was performed to determine precise location of each wall of an building. Finally, roof shape analysis was performed by accumulated slopes along the profiles of the roof top. However, simulated LiDAR data were used for analyzing roof shape because buildings with various shapes of the roof do not exist in the test area. The proposed approach has been tested on the heavily built-up urban residential area. 3D digital vector map produced by digitizing complied aerial photographs was used to evaluate accuracy of the results. Experimental results show efficiency of the proposed methodology for 3D building reconstruction and large scale digital mapping especially for the urban area.

• The Transactions of the Korea Information Processing Society
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• v.2 no.5
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• pp.711-720
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• 1995

This paper describes in object-oriented retrieval framework that is generally designed to store and retrieve the reusable components from the library regardless of the underlying representation of the library. We propose a retrieval framework on visual space so that reuser can identify their location at the library without any previous information of library structure. They can decide the directions of retrieval with the results displayed on the visual space and interact with the library using the defined simple retrieval operation that can assess the library information object. For doing this, 4I model was proposed. Librarian as well as reuser can easily construct the new library on the visual environment. It is the process to give the semantic of the information object. This paper discusses the basic concepts of our 4I model and explains each constituent of our model and shows a simple example of the system.

• Convergence Security Journal
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• v.19 no.3
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• pp.71-79
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• 2019

The demand of smart cars is increasing rapidly. International stand organize such as 3GPP and 5GAA are proposing standard communication protocvols for connected-car, and automotive network infrastructure. But Smart car network have many security threats and more dangerous against the existed wire communication network. Typically, peripheral devices of a smart car may disguise their identity and steal location information and personal information about the vehicle. In addition, the infrastructure elements around smart cars can conspire and put driving cars in danger, threatening lives. This is a very serious security threat. Therefore, in order to solve these problems, we proposed a system that is secure from collusion and tampering attacks using attribute-based authorize delegation method and threshold encryption algorithms. We have demonstrated using a semantic safety model that the proposed system can be safe from collusion attack.

• Journal of Korean Society of Rural Planning
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• v.15 no.3
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• pp.61-79
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• 2009

This study discusses developing ecological trails and route alignment in mountainous rural area. Through a process of ecological resources survey, ecological trails and route alignment has been established. Mainly, by focusing on ecological resources in rural areas, it was indifferent to their own ecological resource and charm to make it unique strengths. Based on survey the results, Natural ecology resources, there were the climate factor, surface, geological, terrain analysis. Furthermore, ecological resources were researched and analyzed the elements of it, distribution of resources, types, location, semantic analysis. The results are expressed on the map and recorded by taking pictures. Plant ecosystem, there were actual vegetation, land use, flora analysis. Wild animal ecosystem, it was checked and recorded on 1/1,000 map partition the emergence of wild birds, the number of species distributed by foraging guild, the emergence of amphibians, reptile, mammals and insect species. The site is chosen as rural theme village in 2007, base on their own rich ecological and landscape resources. Therefore, we carried out ecological trails and route alignment plan in accordance with analyzed the natural ecological resource and after setting up the basic goal, ecological trail has been composed and planting has done and direction.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.1-7
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• 2006

Recently, studies of relevance feedback to increase the performance of image retrieval has been activated. In this Paper a new region weighting method in region based image retrieval with relevance feedback is proposed to reduce the semantic gap between the low level feature representation and the high level concept in a given query image. The new weighting method determines the importance of regions according to the spatial locations of regions in an image. Experimental results demonstrate that the retrieval quality of our method is about 18% in recall better than that of area percentage approach. and about 11% in recall better than that of region frequency weighted by inverse image frequency approach and the retrieval time of our method is a tenth of that of region frequency approach.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.111-121
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• 2021

As the main carrier of information, digital image is becoming more and more important. However, with the popularity of image acquisition equipment and the rapid development of image editing software, in recent years, digital image counterfeiting incidents have emerged one after another, which not only reduces the credibility of images, but also brings great negative impacts to society and individuals. Image copy-paste tampering is one of the most common types of image tampering, which is easy to operate and effective, and is often used to change the semantic information of digital images. In this paper, a method to protect the authenticity and integrity of image content by studying the tamper detection method of image copy and paste was proposed. In view of the excellent learning and analysis ability of deep learning, two tamper detection methods based on deep learning were proposed, which use the traces left by image processing operations to distinguish the tampered area from the original area in the image. A series of experimental results verified the rationality of the theoretical basis, the accuracy of tampering detection, location and classification.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.109-123
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• 2024

Research into vision-based end-to-end autonomous driving systems utilizing deep learning and reinforcement learning has been steadily increasing. These systems typically encode continuous and high-dimensional vehicle states, such as location, velocity, orientation, and sensor data, into latent features, which are then decoded into a vehicular control policy. The complexity of urban driving environments necessitates the use of state representation learning through networks like Variational Autoencoders (VAEs) or Convolutional Neural Networks (CNNs). This paper analyzes the impact of different image state encoding methods on reinforcement learning performance in autonomous driving. Experiments were conducted in the CARLA simulator using RGB images and semantically segmented images captured by the vehicle's front camera. These images were encoded using VAE and Vision Transformer (ViT) networks. The study examines how these networks influence the agents' learning outcomes and experimentally demonstrates the role of each state representation technique in enhancing the learning efficiency and decision- making capabilities of autonomous driving systems.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.34-42
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• 2008

The control points are important assets of countries which express the most accurate location information that is used in surveying land and other measurements. The location information has played an important role in our daily lives with the development of ubiquitous technology. While many researchers have recently applied new technology like RFID(Radio-Frequency Identification) to the effective management of control points, the research into data retrieval and the interoperability of control point data is still primitive step. Therefore, we construct a data modeling to effectively manage control points using ontology data structure and focus on semantic retrieval method. Our retrieval system can provide the inferred and associated information among data using Prot$\acute{e}$g$\acute{e}$-OWL tool. Our system has advantages in reducing the number of repeated queries by hierarchy searching and improving the searching time by association searching. Also, we propose an effective method to construct retrieval systems being able to edit items of categories and properties without editing the related codes.