• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.203-208
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• 2006

The management of image information settles as an important field with the advent of multimedia age and we are in need of the effective retrieval method to manage systematically image information. This paper has complemented the problem caused by the absence of space information that is a weak point of the existing color histogram method by assigning regions of features, and raised accuracy by adding texture and shape information. And existing methods using multiple features have problems that the retrieval process is embarrassed because each weight is set up manually. So we has solved these problems by assignment of weight applying fuzzy integral. As a result of experimenting with 1,000 color images, the proposed method showed better precision and recall than the existing method.

• Journal of Biosystems Engineering
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• v.32 no.4
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• pp.256-262
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• 2007

Image processing systems have been used to measure the plant parameters such as size, shape and structure of plants. There are yet some limited applications for evaluating plant colors due to illumination conditions. This study was focused to present adaptive methods to analyze plant leaf color regardless of illumination conditions. Color patches attached on the calibration bars were selected to represent leaf colors of lettuces and to test a possibility of health monitoring of lettuces. Repeatability of assigning leaf colors to color patches was investigated by two-tailed t-test for paired comparison. It resulted that there were no differences of assignment histogram between two images of one lettuce that were acquired at different light conditions. It supported that use of the calibration bars proposed for leaf color analysis provided color constancy, which was one of the most important issues in a video color analysis. A health discrimination equation was developed to classify lettuces into one of two classes, SOUND group and POOR group, using the machine vision. The classification accuracy of the developed health discrimination equation was 80.8%, compared to farmers' decision. This study could provide a feasible method to develop a standard color chart for evaluating leaf colors of plants and plant health monitoring system using the machine vision.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.73
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• pp.21-42
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• 2017

A BPO is an irrevocable undertaking given by an Obligor Bank acting on behalf of the buyer to a Recipient Bank acting on behalf of the seller to pay on satisfaction of certain specified conditions. There have been a Trade Service Utility(TSU), a Transaction Matching Application(TMA) and ISO 20022 TSMT messages that core electronic technical systems linked to the BPO. As a key usefulness of the BPO, it brings to market an alternative means of satisfying the risk mitigation, financing and information management needs of banks and businesses engaged in trade. That is, corporates can spread the risk among multiple Obligor Banks by requesting multiple BPOs for the same trade transaction not to exceed the value of the initial transaction. Since the BPO replaces the manual document checking process with the electronic matching of data, buyers and sellers will benefit from significantly increased accuracy and objectivity. By using BPO, buyers and sellers can become trusted counterparties by demonstrating reliability and giving sellers the assurance of being paid on time as per the payment terms and conditions agreed. When compared to L/C, the BPO requires submission of data only. This requires a change of practice of those accustomed to dealing with physical documentation. The beneficiary of a BPO is the Recipient Bank which is always the Seller's Bank. In the meantime, banks will need to agree between themselves that the URBPO 750 will be applied, modified or excluded. However, customers of banks will face low transactional costs due to a fully automated process and standardized data formats used in international trade documentation. There is no amendment and cancellation rules in the URBPO 750s, but only have Assignment of Proceeds rules. As a result, the BPO is likely to enable new business opportunities, lower costs, fast transaction process and strengthen key customer relationships.

• Journal of Microbiology and Biotechnology
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• v.22 no.8
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• pp.1054-1058
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• 2012

In order to predict biologically significant attributes such as function from protein sequences, searching against large databases for homologous proteins is a common practice. In particular, BLAST and HMMER are widely used in a variety of biological fields. However, sequence-homologous proteins determined by BLAST and proteins having the same domains predicted by HMMER are not always functionally equivalent, even though their sequences are aligning with high similarity. Thus, accurate assignment of functionally equivalent proteins from aligned sequences remains a challenge in bioinformatics. We have developed the FEP-BH algorithm to predict functionally equivalent proteins from protein-protein pairs identified by BLAST and from protein-domain pairs predicted by HMMER. When examined against domain classes of the Pfam-A seed database, FEP-BH showed 71.53% accuracy, whereas BLAST and HMMER were 57.72% and 36.62%, respectively. We expect that the FEP-BH algorithm will be effective in predicting functionally equivalent proteins from BLAST and HMMER outputs and will also suit biologists who want to search out functionally equivalent proteins from among sequence-homologous proteins.

• Structural Engineering and Mechanics
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• v.37 no.6
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• pp.671-684
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• 2011

Deciding on an optimal sensor placement (OSP) is a common problem encountered in many engineering applications and is also a critical issue in the construction and implementation of an effective structural health monitoring (SHM) system. The present study focuses with techniques for selecting optimal sensor locations in a sensor network designed to monitor the health condition of Dalian World Trade Building which is the tallest in the northeast of China. Since the number of degree-of-freedom (DOF) of the building structure is too large, multi-modes should be selected to describe the dynamic behavior of a structural system with sufficient accuracy to allow its health state to be determined effectively. However, it's difficult to accurately distinguish the translational and rotational modes for the flexible structures with closely spaced modes by the modal participation mass ratios. In this paper, a new method of the OSP that computing the mode shape matrix in the weak axis of structure by the simplified multi-DOF system was presented based on the equivalent rigidity parameter identification method. The initial sensor assignment was obtained by the QR-factorization of the structural mode shape matrix. Taking the maximum off-diagonal element of the modal assurance criterion (MAC) matrix as a target function, one more sensor was added each time until the maximum off-diagonal element of the MAC reaches the threshold. Considering the economic factors, the final plan of sensor placement was determined. The numerical example demonstrated the feasibility and effectiveness of the proposed scheme.

• KIISE Transactions on Computing Practices
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• v.21 no.3
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• pp.247-256
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• 2015

Since the Gulf War, air power has played a key role. However, the effect of high-tech weapons, such as laser-guided bombs and electronic optical equipment, drops significantly if they do not match the weather conditions. So, aircraft that are assigned to carry laser-guided bombs must replace these munitions during bad weather conditions. But, there are no objective criteria for when weapons should be replaced. Therefore, in this paper, we propose an algorithm to predict the hit rate of laser-guided bombs using cloud image processing. In order to verify the accuracy of the algorithm, we applied the weather conditions that may affect laser-guided bombs to simulated flight equipment and executed simulated weapon release, then collected and analyzed data. Cloud images appropriate to the weather conditions were developed, and applied to the algorithm. We confirmed that the algorithm can accurately predict the hit rate of laser-guided bombs in most weather conditions.

• Journal of the Korean Society for information Management
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• v.22 no.1 s.55
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• pp.191-208
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• 2005

This study utilizes various approaches for new topic detection in the process of assigning and updating descriptors, which is a representation method of the knowledge structure. Particularly in the case of occurring changes on the knowledge structure due to the appearance and development of new topics in specific study areas, new topic detection can be applied to solving the impossibility or limitation of the existing index terms in representing subject concepts. This study confirms that the majority of newly developing topics in information science are closely associated with each other and are simultaneously in the phase of growth and development. Also, this study shows the possibility that the use of candidate descriptor lists generated by new topic detection methods can be an effective tool in assisting indexers. In particular. the provision of candidate descriptor lists to help assignment of appropriate descriptors will contribute to the improvement of the effectiveness and accuracy of indexing.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.8
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• pp.335-342
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• 2013

Nowadays, the traffic type and behavior are extremely diverse due to the growth of network speed and the appearance of various services on Internet. For efficient network operation and management, the importance of application-level traffic identification is more and more increasing in the area of traffic analysis. In recent years traffic identification methodology using statistical features of traffic flow has been broadly studied. However, there are several problems to be considered in the identification methodology base on statistical features of flow to improve the analysis accuracy. In this paper, we recognize these problems by analyzing the ground-truth traffic and propose the solution of these problems. The four problems considered in this paper are the distance measurement of features, the selection of the representative value of features, the abnormal behavior of TCP sessions, and the weight assignment to the feature. The proposed solutions were verified by showing the performance improvement through experiments in campus network.

• Korean Journal of Remote Sensing
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• v.20 no.6
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• pp.383-396
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• 2004

The application of spatial statistics to obtain the spatial uncertainty distributions in classification of remote sensing images is investigated in this paper. Two quantitative methods are presented for describing two kinds of uncertainty; one related to class assignment and the other related to the connection of reference samples. Three quantitative indices are addressed for the first category of uncertainty. Geostatistical simulation is applied both to integrate the exhaustive classification results with the sparse reference samples and to obtain the spatial uncertainty or accuracy distributions connected to those reference samples. To illustrate the proposed methods and to discuss the operational issues, the experiment was done on a multi-sensor remote sensing data set for supervised land-cover classification. As an experimental result, the two quantitative methods presented in this paper could provide additional information for interpreting and evaluating the classification results and more experiments should be carried out for verifying the presented methods.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.6
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• pp.49-59
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• 2008

SIFT(Scale Invariant Feature Transform) is an algorithm to extract vectors at pixels around keypoints, in which the pixel colors are very different from neighbors, such as vortices and edges of an object. The SIFT algorithm is being actively researched for various image processing applications including 3-D image constructions, and its most computation-intensive stage is a keypoint localization. In this paper, we develope a fixed-point model of the keypoint localization and propose its efficient hardware architecture for embedded applications. The bit-length of key variables are determined based on two performance measures: localization accuracy and error rate. Comparing with the original algorithm (implemented in Matlab), the accuracy and error rate of the proposed fixed point model are 93.57% and 2.72% respectively. In addition, we found that most of missing keypoints appeared at the edges of an object which are not very important in the case of keypoints matching. We estimate that the hardware implementation will give processing speed of $10{\sim}15\;frame/sec$, while its fixed point implementation on Pentium Core2Duo (2.13 GHz) and ARM9 (400 MHz) takes 10 seconds and one hour each to process a frame.