• Spatial Information Research
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• v.5 no.2
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• pp.147-160
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• 1997

"The "Map Algebra", beeing recognized as a viable theoretical framework for GIS (Geographica Infonnation System), models map layers as "operands" which are the basic unit of geo-processing, and a variety of GIS commands as "operators." In this paper, we attempt at lifting some limitations of map algebras proposed in GIS literature. First, we model map layer as "function" such that we may employ the notion of meta operator (or, higher-order funtion) available in the functional programming paradigm. This approach provides map algebraic language with "programmability" needed in GIS user language. Second, we extend the semantics of, and improve on the sytactic structure of map algebraic language. Mer the data model and language associated with map algebra are formalized, we proceed to design and implement a prototype of map algebraic processor. The parser of the language in our prototype plays the role of transforming the native and heterogeneous user language of current GISs into a canonical map algebraic language. The prototype, named "MapSee" is a proof-of-concept system for the ideas we propsed in this paper. We believe that the uniform interface based on the map algebraic language will make promising infrastructure to support "Internet GIS." This is because the uniform but powerful interface through the Web clients allow access to both geo-data and geo-processing resources distributed over the network.to both geo-data and geo-processing resources distributed over the network.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.123-136
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• 2005

We propose a recognition system for superimposed patterns based on selective attention model and SVM which produces better performance than artificial neural network. The proposed selective attention model includes attention layer prior to SVM which affects SVM's input parameters. It also behaves as selective filter. The philosophy behind selective attention model is to find the stopping criteria to stop training and also defines the confidence measure of the selective attention's outcome. Support vector represents the other surrounding sample vectors. The support vector closest to the initial input vector in consideration is chosen. Minimal euclidean distance between the modified input vector based on selective attention and the chosen support vector defines the stopping criteria. It is difficult to define the confidence measure of selective attention if we apply common selective attention model, A new way of doffing the confidence measure can be set under the constraint that each modified input pixel does not cross over the boundary of original input pixel, thus the range of applicable information get increased. This method uses the following information; the Euclidean distance between an input pattern and modified pattern, the output of SVM, the support vector output of hidden neuron that is the closest to the initial input pattern. For the recognition experiment, 45 different combinations of USPS digit data are used. Better recognition performance is seen when selective attention is applied along with SVM than SVM only. Also, the proposed selective attention shows better performance than common selective attention.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.187-198
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• 2004

The World-Wide Web is the largest distributed Information space and has grown to encompass diverse information resources. However, although Web is growing exponentially, the individual's capacity to read and digest contents is essentially fixed. From the view point of Web users, they can be confused by explosion of Web information, by constantly changing Web environments, and by lack of understanding needs of Web users. In these Web environments, mining traversal patterns is an important problem in Web mining with a host of application domains including system design and Information services. Conventional traversal pattern mining systems use the inter-pages association in sessions with only a very restricted mechanism (based on vector or matrix) for generating frequent k-Pagesets. We develop a family of novel algorithms (termed WebPR - Web Page Recommend) for mining frequent traversal patterns and then pageset to recommend. Our algorithms provide Web users with new page views, which Include pagesets to recommend, so that users can effectively traverse its Web site. The main distinguishing factors are both a point consistently spanning schemes applying inter-pages association for mining frequent traversal patterns and a point proposing the most efficient tree model. Our experimentation with two real data sets, including Lady Asiana and KBS media server site, clearly validates that our method outperforms conventional methods.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.97-106
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• 2002

In 3GPP2 standard, MIP is used and a PDSN performs the function of FA to support macro mobility. When a MS is roaming from a PDSN area to another, the mobility supported is called macro mobility, while it is called micro mobility when a MS is roaming from a RN area to another in a PDSN area. Since a PDSN performs the function of FA in 3GPP2 standard, it is possible to support mobility but its mechanism is actually for supporting macro mobility, not for micro mobility, thus it is weak in processing fast and seamless handoff to support micro mobility. In this paper, we suggest the seamless handoff algorithm barred on multicast group mechanism to support micro mobility. Depending on the moving direction and velocity of a MS, the suggested algorithm constructs a multicast group of RNs on the forecasted MS's moving path, and maximally delays RNs'joining to a multicast group to increase the network efficiency. Moreover, to resolve the buffer overhead problem of the existent multicast scheme, the algorithm suggests that each RN buffers data only after the forecasted handoff time. To prove deadlock freeness and liveness of the algorithm. we use state transition diagrams, a Petri-net modeling and its reachability tree. Then, we evaluate the performance by simulation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.190-196
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• 2020

FRACAS(Failure Reporting, Analysis and Corrective Action System) has been applied in various industries to improve the reliability of the systems. FRACAS is effective in improving reliability by repeating failure analysis, proper corrective action, and result verification for identified failures. However, FRACAS has many limitations in terms of process, data collection and management to be integrated into the existing development environment. In the domestic defense industry, studies on the development of FRACAS system and process improvement have been conducted to solve the difficulties of applying FRACAS, but most of them are concentrated in the operation/maintenance phase. Since FRACAS should be conducted in consideration of TLCSM(Total Life Cycle System Management), it is necessary to study the reference architecture so that FRACAS can be applied from the early design phase. In this paper, we studied the TLCSM-based integrated architecture considering the system life cycle phases, FRACAS closed-loop process, and FRACAS essentials in order to effectively apply FRACAS throughout the life cycle of defense systems. The proposed architecture was used as a reference model for FRACAS in a shipboard combat system.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.1
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• pp.9-18
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• 2018

Recently, the use of image stitching technology has been increasing as the number of contents based on virtual reality increases. Image Stitching is a method for matching multiple images to produce a high resolution image and a wide field of view image. The image stitching is used in various fields beyond the limitation of images generated from one camera. Image Stitching detects feature points and corresponding points to match multiple images, and calculates the homography among images using the RANSAC algorithm. Generally, corresponding points are needed for calculating conversion relation. However, the corresponding points include various types of noise that can be caused by false assumptions or errors about the conversion relationship. This noise is an obstacle to accurately predict the conversion relation. Therefore, RANSAC algorithm is used to construct an accurate conversion relationship from the outliers that interfere with the prediction of the model parameters because matching methods can usually occur incorrect correspondence points. In this paper, we propose an algorithm that extracts more accurate inliers and computes accurate transformation relations by using correspondence point relation information used in RANSAC algorithm. The correspondence point relation information uses distance ratio between corresponding points used in image matching. This paper aims to reduce the processing time while maintaining the same performance as RANSAC.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.552-560
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• 2021

Currently, the domestic aquaculture industry is pursuing smartization, but it is still proceeding with human subjective judgment in many processes in the aquaculture stage. The prerequisite for the smart aquaculture industry is to effectively grasp the condition of fish in the farm. If real-time monitoring is possible by identifying the number of fish populations, size, pathways, and speed of movement, various forms of automation such as automatic feed supply and disease determination can be carried out. In this study, we proposed an algorithm to identify the state of fish in real time using underwater video data. The fish detection performance was compared and evaluated by applying the latest deep learning-based object detection models, and an algorithm was proposed to measure fish object identification, path tracking, and moving speed in continuous image frames in the video using the fish detection results. The proposed algorithm showed 92% object detection performance (based on F1-score), and it was confirmed that it effectively tracks a large number of fish objects in real time on the actual test video. It is expected that the algorithm proposed in this paper can be effectively used in various smart farming technologies such as automatic feed feeding and fish disease prediction in the future.

• Smart Media Journal
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• v.11 no.10
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• pp.89-96
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• 2022

An open domain machine reading comprehension is a model that adds a function to search paragraphs as there are no paragraphs related to a given question. Document searches have an issue of lower performance with a lot of documents despite abundant research with word frequency based TF-IDF. Paragraph selections also have an issue of not extracting paragraph contexts, including sentence characteristics accurately despite a lot of research with word-based embedding. Document reading comprehension has an issue of slow learning due to the growing number of parameters despite a lot of research on BERT. Trying to solve these three issues, this study used BM25 which considered even sentence length and InferSent to get sentence contexts, and proposed an open domain machine reading comprehension with ALBERT to reduce the number of parameters. An experiment was conducted with SQuAD1.1 datasets. BM25 recorded a higher performance of document research than TF-IDF by 3.2%. InferSent showed a higher performance in paragraph selection than Transformer by 0.9%. Finally, as the number of paragraphs increased in document comprehension, ALBERT was 0.4% higher in EM and 0.2% higher in F1.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.447-455
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• 2017

At the modern industry, the composite material has been widely used. Particularly, the material of carbon fiber reinforced plastic hardened with resin on the basis of fiber is excellent. As the specific strength and rigidity are also superior, it receives attention as the light material. Among these materials, the carbon fiber reinforced plastic using carbon fiber has the superior mechanical property different from another fiber. So, it is utilized in vehicle and airplane at which high strength and light weight are needed at the same time. In this paper, the tensile property due to the fiber design is investigated through the analysis study with CT specimen composed of carbon plastic reinforced plastic. At the stress analysis of CFRP composite material with hole, the fracture trend at the tensile environment is examined. Also, it is shown that the lowest stress value happens and the deformation energy of the pre-crack becomes lowest at the analysis model composed of the stacking angle of 60° through the result due to the stacking angle. On the basis of this study result, it is thought to apply the foundation data to anticipate the fracture configuration at the structure applied with the practical experiment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.236-238
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• 2022

According to the current Road Traffic Act, the 2020 amendment bill is currently in effect as a system that designates vehicle types for each lane for the purpose of securing road use efficiency and traffic safety. When comparing the number of traffic accident fatalities per 10,000 vehicles in Germany and Korea, the number of traffic accident deaths in Germany is significantly lower than in Korea. The representative case of the German autobahn, which did not impose a speed limit, suggests that Korea's speeding laws are not the only answer to reducing the accident rate. The designated lane system, which is observed in accordance with the keep right principle of the Autobahn Expressway, plays a major role in reducing traffic accidents. Based on this fact, we propose a traffic enforcement system to crack down on vehicles violating the designated lane system and improve the compliance rate. We develop a designated lane enforcement system that recognizes vehicle types using Yolo5, a deep learning object recognition model, recognizes license plates and lanes using OpenCV, and stores the extracted data in the server to determine whether or not laws are violated.Accordingly, it is expected that there will be an effect of reducing the traffic accident rate through the improvement of driver's awareness and compliance rate.