• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.179-190
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• 2009

Travel time is one of the most important traffic parameters to evaluate operational performance of freeways. A variety of methods have been proposed to estimate travel times. One feasible solution to estimating travel times is to utilize existing loop detector-based infrastructure since the loops are the most widely deployed detection system in the world. This study proposed a new approach to estimate travel times for freeways. Inductive vehicle signatures extracted from the loop detectors were used to match vehicles from upstream and downstream stations. Ground-truthing was also conducted to systematically evaluate the performance of the proposed algorithm by recognizing individual vehicles captured by video cameras placed at upstream and downstream detection stations. A lexicographic optimization method vehicle reidentification algorithm was developed. Vehicle features representing the characteristics of individual vehicles such as vehicle length and interpolations extracted from the signature were used as inputs of the algorithm. Parameters associated with the signature matching algorithm were calibrated in terms of maximizing correct matching rates. It is expected that the algorithm would be a useful method to estimate freeway link travel times.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.251-275
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• 2011

In this paper, we propose a novel kernel called a semantic parse tree kernel that extends the parse tree kernel previously studied to extract protein-protein interactions(PPIs) and shown prominent results. Among the drawbacks of the existing parse tree kernel is that it could degenerate the overall performance of PPI extraction because the kernel function may produce lower kernel values of two sentences than the actual analogy between them due to the simple comparison mechanisms handling only the superficial aspects of the constituting words. The new kernel can compute the lexical semantic similarity as well as the syntactic analogy between two parse trees of target sentences. In order to calculate the lexical semantic similarity, it incorporates context-based word sense disambiguation producing synsets in WordNet as its outputs, which, in turn, can be transformed into more general ones. In experiments, we introduced two new parameters: tree kernel decay factors, and degrees of abstracting lexical concepts which can accelerate the optimization of PPI extraction performance in addition to the conventional SVM's regularization factor. Through these multi-strategic experiments, we confirmed the pivotal role of the newly applied parameters. Additionally, the experimental results showed that semantic parse tree kernel is superior to the conventional kernels especially in the PPI classification tasks.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.43-50
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• 2018

Biometric information computing is greatly influencing both a computing system and Big-data system based on the bio-information system that combines bio-signal sensors and bio-information processing. Unlike conventional data formats such as text, images, and videos, biometric information is represented by text-based values that give meaning to a bio-signal, important event moments are stored in an image format, a complex data format such as a video format is constructed for data prediction and analysis through time series analysis. Such a complex data structure may be separately requested by text, image, video format depending on characteristics of data required by individual biometric information application services, or may request complex data formats simultaneously depending on the situation. Since previous bio-information processing computing systems depend on conventional computing component, computing structure, and data processing method, they have many inefficiencies in terms of data processing performance, transmission capability, storage efficiency, and system safety. In this study, we propose an improved biosensing converged big data computing architecture to build a platform that supports biometric information processing computing effectively. The proposed architecture effectively supports data storage and transmission efficiency, computing performance, and system stability. And, it can lay the foundation for system implementation and biometric information service optimization optimized for future biometric information computing.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.2
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• pp.311-316
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• 2016

Network intrusion detection system based on machine learning method such as artificial neural network is quite dependent on the selected features in terms of accuracy and efficiency. Nevertheless, choosing the optimal combination of features, which guarantees accuracy and efficienty, from generally used many features to detect network intrusion requires extensive computing resources. In this paper, we deal with a optimal feature selection problem to determine 6 denial service attacks and normal usage provided by NSL-KDD data. We propose a optimal feature selection algorithm. Proposed algorithm is based on the multi-start local search algorithm, one of representative meta-heuristic algorithm for solving optimization problem. In order to evaluate the performance of our proposed algorithm, comparison with a case of all 41 features used against NSL-KDD data is conducted. In addtion, comparisons between 3 well-known machine learning methods (multi-layer perceptron., Bayes classifier, and Support vector machine) are performed to find a machine learning method which shows the best performance combined with the proposed feature selection method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.29-38
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• 2012

The noise generated in the process of obtaining the medical image acts as the element obstructing the image interpretation and diagnosis. To restore the true image from the image polluted from the noise, the total variation optimization algorithm was proposed by the R.O. F (L.Rudin, S Osher, E. Fatemi). This method removes the noise by fitting the balance of the regularity and fidelity. However, the blurring phenomenon of the border area generated in the process of performing the iterative operation cannot be avoided. In this paper, we propose the adaptive total variation method by mapping the control parameter to the proposed transfer function for minimizing boundary error. The proposed transfer function is determined by the noise variance and the local property of the image. The proposed method was applied to 464 tooth images. To evaluate proposed method performance, PSNR which is a indicator of signal and noise's signal power ratio was used. The experimental results show that the proposed method has better performance than other methods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6A
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• pp.417-424
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• 2011

This study focused on development of 60 m span PSC girder considering not only structural performance, but also economical efficiency and constructability including from the improvement of cross-section to the tendon profiles in sequence. Bulb-T type cross section was derived from optimization and actual possibilities to design a bridge were assessed through cross section evaluation. Tendons were also arranged efficiently so that the girder could resist the service load effectively. After developed girder was applied to a sample bridge, result of finite element analysis proved all load steps were satisfied with the allowable stress. Furthermore, it seemed that sufficient redundancy will be available to design a bridge safely. Based on these, a full-scale 60 m span girder was fabricated and 4 point bending test was performed. An initial crack occurred over twice of the service load in this experiment, which establishes adequate structural performance. 60 m span Half-Decked PSC girder developed in this study has a lower height for the given span which resulted from cross section improvement and efficient tendon layout. This girder also has not only the structural advantage, but also advantages in economical efficiency and constructability.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.1
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• pp.59-67
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• 2013

Complex-shaped tall building causes many structural challenges due to its structural characteristics regarding inclined members and complexed shape. This paper is aimed at development of design process using computational-platform which is effective design tool for responding frequent design changes, particularly as to overseas projects. StrAuto, a parametric structural modeling and optimizing system, provides the optimized alternatives according to design intent and realize a swift process converting a series of structural information necessary to nonlinear analytical models. The application of the process was to a 45-story hotel building in Ulanbator, Mongolia adopting shear wall and special moment frame with outrigger systems. To investigate the safety of lateral force resisting system against maximum considered earthquake(MCE), nonlinear response history analysis was conducted using StrAuto.

• The KIPS Transactions:PartA
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• v.13A no.4 s.101
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• pp.275-288
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• 2006

Rapid design space exploration is crucial to customizing embedded system design for exploiting the application behavior. As the time-to-market becomes a key concern of the design, the approach based on an application specific instruction-set processor (ASIP) is considered more seriously as one alternative design methodology. In this approach, the instruction set architecture (ISA) for a target processor is frequently modified to best fit the application with regard to code size and speed. Two goals of this paper is to introduce our new retargetable compiler and how it has been used in ASIP-based design space exploration for a popular digital signal processing (DSP) application. Newly developed retargetable compiler provides not only the functionality of previous retargetable compilers but also visualizes the features of the application program and profiles it so that it can help architecture designers and application programmers to insert new application specific instructions into target architecture for performance increase. Given an initial RISC-style ISA for the target processor, we characterized the application code and incrementally updated the ISA with more application specific instructions to give the compiler a better chance to optimize assembly code for the application. We get 32% performance increase and 20% program size reduction using 6 audio codec specific instructions from retargetable compiler. Our experimental results manifest a glimpse of evidence that a higgly retargetable compiler is essential to rapidly prototype a new ASIP for a specific application.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3792-3799
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• 2012

The dedusting characteristics of pulse air jet type dedusting system which is widely applied in the industries were identified by utilizing the computational fluid dynamics (CFD) and the dedusting performance in modified shape of dedusting unit was compared in this study. The review on the dedusting air volume, air stream distribution and inflow velocity distribution on each shape of dedusting part showed that the case of installing the nozzle on the blow tube (Case-3) and the case of installing the double intaking tube to the venturi (Case-4 and Case-5) were more excellent than the structure (Case-1) which is widely applied in the field in its amplification effect on the air volume and extension of stream width. The specification of venturi was decided to apply the selected Case-5 for the option of the commercial back filter. It is considered that the dedusting air volume will be maintained in maximum in the case of 50 mm and 90 mm for the diameter of internal and external intaking pipe respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.1-6
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• 2017

Recent researches on radio frequency energy harvesting networks(RF-EHNs) with limited energy resource like battery have been focusing on the development of a new scheme that can effectively extend the whole lifetime of a network to semipermanent. In order for considerable increase both in the amount of energy obtained from radio frequency energy harvesting and its charging effectiveness, it is very important to design a network that supports energy harvesting and data transfer simultaneously with the full consideration of various characteristics affecting the performance of a RF-EHN. In this paper, we proposes an interference-based charging aware routing protocol(ICARP) that utilizes interference information and charging time to maximize the amount of energy harvesting and to minimize the end-to-end delay from a source to the given destination node. To accomplish the research objectives, this paper gives a design of ICARP adopting new network metrics such as interference information and charging time to minimize end-to-end delay in energy harvesting wireless networks. The proposed method enables a RF-EHN to reduce the number of packet losses and retransmissions significantly for better energy consumption. Finally, simulation results show that the network performance in the aspects of packet transmission rate and end-to-end delay has enhanced with the comparison of existing routing protocols.