• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.336-342
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• 2003

Noise predictive maximum likelihood(NPML) detector embeds noise prediction/whitening process in branch metric calculation of Viterbi detector and improves the reliability of branch metric computation. Therefore, PRML detector with a noise predictor achieves some performance improvement and has an advantage of low complexity. This thesis random sequences are applied to linear channel. In perpendicular magnetic recording density KP=2.5, NP(121)ML and NP(1221)ML detection system which is based on a noise predictive PR-equalized signal are evaluated by the Performance through a computing simulation. Therefore, NPML systems are implemented and are verified by VHDL.

• International Journal of Fluid Machinery and Systems
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• v.3 no.4
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• pp.379-385
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• 2010

We developed a high-efficiency, wide-operating-range centrifugal blower stage to meet the demand for reduced total energy-consumption in sewage treatment plants. We improved the efficiency of the two-dimensional impeller using a shape optimization tool and one-dimensional performance prediction tool. A limit of the throat deceleration ratio was set to maintain the stall-margin of the impeller. The low solidity vaned diffuser and return channel were designed using a sensitivity analysis with orthogonal arrays and three-dimensional steady flow simulations. The low solidity diffuser was designed in order to improve the performance in the low-flow-rate region. The return channel was designed so that the total pressure loss in the return channel was minimized. Model tests of both the conventional and optimized blower stages were carried out, and the efficiency and operating range of both stages were compared. The optimized blower stage improved in stage efficiency by 3% and in operating range by 5% compared with the conventional blower stage.

• Atmosphere
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• v.29 no.1
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• pp.1-12
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• 2019

For the allergy patient who needs to know the situation about the extent of pollen risk, the National Institute of Meteorological Sciences developed a pollen forecasting system based on the Community Multiscale Air Quality Modeling (CMAQ). In the old system, pollen emission from the oak was estimated just based on the airborne concentration and meteorology factors, resulted in high uncertainty. For improving the quality of current pollen forecasting system, therefore the estimation of pollen emission is now corrected based on the observation of pollen emission at the oak forest to better reflect the real emission pattern. In this study, the performance of the previous (NIMS2014) and current (NIMS2016) model system was compared using observed oak pollen concentration. Daily pollen concentrations and emissions were simulated in pollen season 2016 and accuracy of onset and end of pollen season were evaluated. In the NIMS2014 model, pollen season was longer than actual pollen season; The simulated pollen season started 6 days earlier and finished 13.25 days later than the actual pollen season. The NIMS2016 model, however, the simulated pollen season started only 1.83 days later, and finished 0.25 days later than the actual pollen season, showing the improvement to predict the temporal range of pollen events. Also, the NIMS2016 model shows better performance for the prediction of pollen concentration, while there is a still large uncertainty to capture the maximum pollen concentration at the target site. Continuous efforts to correct these problems will be required in the future.

• Steel and Composite Structures
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• v.46 no.1
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• pp.75-92
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• 2023

The novel composite cold-formed steel (CFS)/engineered cementitious composites (ECC) beams have been recently presented. The new composite section exhibited superior structural performance as a flexural member, benefiting from the lightweight thin-walled CFS sections with improved buckling and torsional properties due to the restraints provided by thinlayered ECC. This paper investigated the shear performance of the new composite CFS/ECC section. Twenty-eight simply supported beams, with a shear span-to-depth ratio of 1.0, were assembled back-to-back and tested under a 3-point loading scheme. Bare CFS, composite CFS/ECC utilising ECC with Polyethylene fibres (PE-ECC), composite CFS/MOR, and CFS/HSC utilising high-strength mortar (MOR) and high-strength concrete (HSC) as replacements for PE-ECC were compared. Different failure modes were observed in tests: shear buckling modes in bare CFS sections, contact shear buckling modes in composite CFS/MOR and CFS/HSC sections, and shear yielding or block shear rupture in composite CFS/ECC sections. As a result, composite CFS/ECC sections showed up to 96.0% improvement in shear capacities over bare CFS, 28.0% improvement over composite CFS/MOR and 13.0% over composite CFS/HSC sections, although MOR and HSC were with higher compressive strength than PE-ECC. Finally, shear strength prediction formulae are proposed for the new composite sections after considering the contributions from the CFS and ECC components.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.1
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• pp.161-177
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• 2013

High-speed vessels require good resistance and seakeeping performance for safe operations in rough seas. The resistance and seakeeping performance of high-speed vessels varies significantly depending on their hull forms. In this study, three planing hulls that have almost the same displacement and principal dimension are designed and the hydrodynamic characteristics of those hulls are estimated by high-speed model tests. All model ships are deep-V type planing hulls. The bows of no.2 and no.3 model ships are designed to be advantageous for wave-piercing in rough water. No.2 and no.3 model ships have concave and straight forebody cross-sections, respectively. And length-to-beam ratios of no.2 and no.3 models are larger than that of no.1 model. In calm water tests, running attitude and resistance of model ships are measured at various speeds. And motion tests in regular waves are performed to measure the heave and pitch motion responses of the model ships. The required power of no.1 (VPS) model is smallest, but its vertical motion amplitudes in waves are the largest. No.2 (VWC) model shows the smallest motion amplitudes in waves, but needs the greatest power at high speed. The resistance and seakeeping performance of no.3 (VWS) model ship are the middle of three model ships, respectively. And in regular waves, no.1 model ship experiences 'fly over' phenomena around its resonant frequency. Vertical accelerations at specific locations such as F.P., center of gravity of model ships are measured at their resonant frequency. It is necessary to measure accelerations by accelerometers or other devices in model tests for the accurate prediction of vertical accelerations in real ships.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.97-113
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• 2016

Due to the growth of internet data and the rapid development of internet technology, "big data" analysis is actively conducted to analyze enormous data for various purposes. Especially in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of existing structured data analysis. Various studies on sentiment analysis, the part of text mining techniques, are actively studied to score opinions based on the distribution of polarity of words in documents. Usually, the sentiment analysis uses sentiment dictionary contains positivity and negativity of vocabularies. As a part of such studies, this study tries to construct sentiment dictionary which is customized to specific data domain. Using a common sentiment dictionary for sentiment analysis without considering data domain characteristic cannot reflect contextual expression only used in the specific data domain. So, we can expect using a modified sentiment dictionary customized to data domain can lead the improvement of sentiment analysis efficiency. Therefore, this study aims to suggest a way to construct customized dictionary to reflect characteristics of data domain. Especially, in this study, movie review data are divided by genre and construct genre-customized dictionaries. The performance of customized dictionary in sentiment analysis is compared with a common sentiment dictionary. In this study, IMDb data are chosen as the subject of analysis, and movie reviews are categorized by genre. Six genres in IMDb, 'action', 'animation', 'comedy', 'drama', 'horror', and 'sci-fi' are selected. Five highest ranking movies and five lowest ranking movies per genre are selected as training data set and two years' movie data from 2012 September 2012 to June 2014 are collected as test data set. Using SO-PMI (Semantic Orientation from Point-wise Mutual Information) technique, we build customized sentiment dictionary per genre and compare prediction accuracy on review rating. As a result of the analysis, the prediction using customized dictionaries improves prediction accuracy. The performance improvement is 2.82% in overall and is statistical significant. Especially, the customized dictionary on 'sci-fi' leads the highest accuracy improvement among six genres. Even though this study shows the usefulness of customized dictionaries in sentiment analysis, further studies are required to generalize the results. In this study, we only consider adjectives as additional terms in customized sentiment dictionary. Other part of text such as verb and adverb can be considered to improve sentiment analysis performance. Also, we need to apply customized sentiment dictionary to other domain such as product reviews.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.2
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• pp.61-71
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• 2007

The instruction level parallelism, which has been used to improve the performance of processors, expose its limit. The change of a control flow by a branch miss prediction is one of the obstacles that restrict the instruction level parallelism. The single chip multiprocessors have been developed to utilize the thread level parallelism. However, we could not use the maximum performance of the single chip multiprocessor in case of executing the coded programs without considering the multi-thread. In order to overcome the two performance degradation factors, in this paper, we suggest the concurrent branch execution method that applies to the multi-path execution method at a single chip multiprocessor. We executes all two flows of the conditional branch using the idle core processor. Through this, we can improve the processor's efficiency with blocking the control flow termination by the branch instruction and reducing the idle time. We analyze the effects of concurrent branch execution proposed in this paper through the simulation. As a result of that, concurrent branch execution reduces about 20% of idle time and improves the maximum 10% of the branch prediction accuracy. We show that our scheme improves the overall performance of maximum 39% compared to the normal single chip multiprocessor and maximum 27% compared to the superscalar processor.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.5
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• pp.323-334
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• 2020

Since boundary layer transition has a significant impact on the aero-thermodynamic performance of hypersonic flight vehicles, capability of accurate prediction of transition location is essential for design and performance analysis. In this study, γ-Re_θt model is improved to predict transition of hypersonic boundary layers and validated. A coefficient in the production term of the intermittency transport equation that affects the transition onset location is constructed and applied as a function of Mach number, wall temperature, and freestream stagnation temperature based on the similarity numerical solution of compressible boundary layer. To take into account a Mach number dependency of transition onset momentum thickness Reynolds number and transition length, additional correlation equations are determined as function of Mach number and applied to Re_θc and F_length correlations of the baseline model. The suggested model is implemented to a commercial CFD code in consideration of practical use. Analysis of hypersonic flat plate and circular cone boundary layers is carried out by using the model for validation purpose. An improvement of prediction capability with respect to variation of Mach number and unit Reynolds number is identified from the comparison with experimental data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12A
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• pp.1182-1188
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• 2006

Adaptive OFDM(Orthogonal Frequency Division Multiplexing) improves data capacity and system performance over multipath fading by adaptively changing modulation schemes according to channel state information(CSI). To achieve a good performance in adaptive OFDM systems, CSI should be transmitted from receiver to transmitter in real time through feedback channel. However, practically, the CSI feedback delay d which is the sum of the data processing delay and the propagation delay is not negligible and damages to the reliability of CSI such that the performance of adaptive OFDM is degraded. This paper presents an adaptive OFDM system with a multistep predictor on the frequency axis to effectively compensate the multiple feedback delays $d(\geq2)$. Via computer simulation we compare the proposed scheme and existing adaptive OFDM schemes with respect to data capacity and system performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.580-586
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• 2021

The CAT methodology is a numerical analysis technique using CAE. Recently, a methodology of applying artificial intelligence techniques to a simulation has been studied. A previous study compared the deformation results according to the injection molding process using a machine learning technique. Although MLP has excellent prediction performance, it lacks an explanation of the decision process and is like a black box. In this study, data was generated using Autodesk Moldflow 2018, an injection molding analysis software. Several Machine Learning Algorithms models were developed using RapidMiner version 9.5, a machine learning platform software, and the root mean square error was compared. The decision-tree showed better prediction performance than other machine learning techniques with the RMSE values. The classification criterion can be increased according to the Maximal Depth that determines the size of the Decision-tree, but the complexity also increases. The simulation showed that by selecting an intermediate value that satisfies the constraint based on the changed position, there was 7.7% improvement compared to the previous simulation.