• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.239-251
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• 2010

In modern distributed enterprise applications that have multilayered architecture, business entities are a kind of crosscutting concerns running through service components that implements business logic in each layer. When business entities are modified, service components related to them should also be modified so that they can deal with those business entities with new types, even though their functionality remains the same. Our previous paper proposed what we call the DTT (Data Type-Tolerant) component model to efficiently process the variability of business entities, which are data externalized from service components. While the DTT component model, by removing direct coupling between service components and business entities, exempts the need to rewrite service components when business entities are modified, it incurs the burden of implementing data type converters that mediate between them. To solve this problem, this paper proposes a method to use ontology as the metadata of both SCDTs (Self-Contained Data Types) in service components and business entities, and a method to generate data type converter code using the ontology. This ontology-based DTT component model greatly enhances the reusability of service components and the efficiency in processing data variability by allowing the computer to automatically generate data type converters without error.

• Journal of Korea Multimedia Society
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• v.12 no.2
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• pp.209-218
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• 2009

3D backprojection is a kind of reconstruction algorithm to generate volume data consisting of tomographic images, which provides spatial information of the original 3D data from hundreds of 2D projections. The computational time of backprojection increases in proportion to the size of volume data and the number of projection images since the value of every voxel in volume data is calculated by considering corresponding pixels from hundreds of projections. For the reduction of computational time, fast GPU based 3D backprojection methods have been studied recently and the performance of them has been improved significantly. This paper presents two multiple GPU based methods to maximize the parallelism of GPU and compares the efficiencies of two methods by considering both the number of projections and the size of volume data. The first method is to generate partial volume data independently for all projections after allocating a half size of volume data on each GPU. The second method is to acquire the entire volume data by merging the incomplete volume data of each GPU on CPU. The in-complete volume data is generated using the half size of projections after allocating the full size of volume data on each GPU. In experimental results, the first method performed better than the second method when the entire volume data can be allocated on GPU. Otherwise, the second method was efficient than the first one.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.121-129
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• 2021

In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.

• The Transactions of the Korea Information Processing Society
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• v.13 no.8
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• pp.356-366
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• 2024

Users of intelligent robots require access to the status data of the robots for various reasons. The status data of intelligent robots can be generated by combining the status data of the functional agents that constitute the intelligent robot. However, existing intelligent robot systems do not generate the necessary agent status data for creating the status data of intelligent service robots, or they generate it in different ways, making it impossible to collect this information in a uniform manner. Furthermore, these systems have limitations such as collecting the same information redundantly if multiple users request it and only using a single method of communication to deliver robot information, thereby failing to offer the communication methods desired by users. This paper proposes a multi-agent monitoring system for intelligent service robots designed to overcome these limitations. This monitoring system generates status data in response to the actions performed by functional agents, thereby allowing for the unified generation and collection of agent status data. Additionally, the monitoring system resolves data redundancy issues by collecting the necessary data just once, in accordance with user monitoring demands, and delivers status data through a proxy that supports the preferred communication methods of users, thereby providing compatibility with various communication methods. Through experiments, we have verified that this monitoring system can deliver the status data of intelligent robots to multiple users using various communication methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.170-180
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• 2010

With development of the earth's subsurface space, the need for a reliable subsurface spatial model such as a cross-section, boring log is increasing. However, the ground mass was essentially uncertain. To generate model was uncertain because of the shortage of data and the absence of geotechnical interpretation standard(non-statistical uncertainty) as well as field environment variables(statistical uncertainty). Therefore, the current interpretation of the data and the generation of the model were accomplished by a highly trained experts. In this study, a geotechnical ontology model was developed using the current expert experience and knowledge, and the information content was calculated in the ontology hierarchy. After the relative distance between the information contents in the ontology model was combined with the distance between cluster centers, a cluster analysis that considered the geotechnical semantics was performed. In a comparative test of the proposed method, k-means method, and expert's interpretation, the proposed method is most similar to expert's interpretation, and can be 3D-GIS visualization through easily handling massive data. We expect that the proposed method is able to generate the more reasonable subsurface spatial information model without geotechnical experts' help.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.61-76
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• 2015

In general, we have utilized the hierarchical concept tree as a crucial data structure for indexing huge amount of textual data. This paper proposes a generality rank-based method that can automatically develop hierarchical concept structures with the Wikipedia data. The goal of the method is to regard each of Wikipedia articles as a concept and to generate hierarchical relationships among concepts. In order to estimate the generality of concepts, we have devised a special ranking function that mainly uses the number of hyperlinks among Wikipedia articles. The ranking function is effectively used for computing the probabilistic subsumption among concepts, which allows to generate relatively more stable hierarchical structures. Eventually, a set of concept pairs with hierarchical relationship is visualized as a DAG (directed acyclic graph). Through the empirical analysis using the concept hierarchy of Open Directory Project, we proved that the proposed method outperforms a representative baseline method and it can automatically extract concept hierarchies with high accuracy.

• Journal of KIISE
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• v.43 no.12
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• pp.1365-1375
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• 2016

One of the most important capabilities for autonomous service robots working in living environments is to recognize and understand the correct context in dynamically changing environment. To generate high-level context knowledge for decision-making from multiple sensory data streams, many technical problems such as multi-modal sensory data fusion, uncertainty handling, symbolic knowledge grounding, time dependency, dynamics, and time-constrained spatio-temporal reasoning should be solved. Considering these problems, this paper proposes an effective dynamic context management and spatio-temporal reasoning method for intelligent service robots. In order to guarantee efficient context management and reasoning, our algorithm was designed to generate low-level context knowledge reactively for every input sensory or perception data, while postponing high-level context knowledge generation until it was demanded by the decision-making module. When high-level context knowledge is demanded, it is derived through backward spatio-temporal reasoning. In experiments with Turtlebot using Kinect visual sensor, the dynamic context management and spatio-temporal reasoning system based on the proposed method showed high performance.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.1
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• pp.140-148
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• 2004

A novel rapid prototyping (RP) process, a full-automated transfer type variable lamination manufacturing process (Full-automated VLM-ST) has been developed. In the full-automated VLM-ST process, a vacuum chuck and a rectilinear motion system transfer the EPS foam material in the form of the plate with two pilot holes to the rotary supporting stage. The supplied material is then cut into an automated unit shape layer (AUSL) with a desired width, a desired length, a desired slope on the side surface, and a pair of reference shapes, which is called the guide shape (GS)’, including two pilot holes in accordance with CAD data through cutting in two steps using a four-axis synchronized hotwire cutter. Then, each AUSL is stacked by setting each AUSL with two pilot holes in the building plate with two pilot pins, and subsequently, adhesive is applied onto the top surface of the stacked AUSL by a bonding roller and pressure is simultaneously given to the bottom surface of the stacked AUSL. Finally, three-dimensional shapes are rapidly and automatically fabricated. This paper describes the method to generate guide shapes in AUSL data for the full-automated VLM-ST process. In order to examine the applicability of the method to generate guide shapes, three-dimensional shapes, such as a piston shape and a human head shape, are fabricated from the full-automated VLM-ST apparatus.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.2
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• pp.147-155
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• 2013

Proxy re-encryption scheme has advantage where plaintext does not get exposed during re-encryption process. This scheme is popular for sharing server-saved data in case of cloud computing or mobile office that uses server to save data. Since previous proxy re-encryption schemes can use re-encryption key over and over again, it may abuse re-encryption. To solve this problem, conditional proxy re-encryption scheme was proposed. But, it is computationally expensive generate the same number of re-encryption key with the number of condition values. In this paper, we propose an efficient conditional proxy re-encryption scheme in terms of re-encryption key generation. The proposed scheme uses only encryption and decryption process. Therefore it has advantage to generate one re-encryption key for one person. The proposed scheme is secure against chosen-ciphertext attack.

• International Journal of Highway Engineering
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• v.16 no.5
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• pp.91-98
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• 2014

PURPOSES : This study is to develop a automate road mapping system using ARASEO(Automated Road Analysis and Safety Evaluation TOol) for road management. METHODS : The road survey van named ARASEO(Automated Road Analysis and Safety Evaluation TOol) was used to generate highway drawings for Korea National Road number 37 automatically. In order to generate the highway drawings for purpose of road management, it is required to acquired the information for highway alignment, road width and road facilities such as safety barrier and road sign. Therefore the survey van acquired and analyzed the road width, median and guardrail data using rear side laser sensor of ARASEO and recognized the traffic control sign and chevron sign using foreside camera images. Also the highway alignment which is the basic information for highway drawing can be analyzed by acquisition the every 1m positional and attitude data using GPU and IMU sensor and developed algorithm. Finally, in this research the CAD based drawing software was developed to draw highway drawing using the analysis result from ARASEO. RESULTS : This study showed the comparison result of the surveyed road width and drawing data. To make the drawing of the road, we made the Autocad ARX program witch run in CAD menu interface. CONCLUSIONS : Using this program we can create the road center line, every 500m horizontal and vertical ground plan drawing automatically.