• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.145-153
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• 2023

This study emphasizes the essential need in the military for effective measurement and monitoring of soldiers' physical fitness, health, and exercise capabilities to enhance both their overall fitness and combat effectiveness. The effective assessment of physical fitness is considered a core element of management, aligning with principles of modern management. Particularly, preparing soldiers with robust physical fitness is deemed crucial for adapting to dynamic changes on the battlefield. In this research, the RFM (Recency, Frequency, Monetary) customer analysis and clustering methods, validated in e-commerce, are introduced as a basis for applying an AI-driven customer analysis approach to assess military personnel fitness. To achieve this, the study explores the incorporation of the RSC (Reveal, Sustainable, Control) analysis model. This model aims to effectively categorize and monitor military personnel fitness. The application of the RFM technique in the RSC analysis model quantifies and models military fitness, fostering continuous improvement and seeking strategies to enhance the effectiveness of fitness management. Through these methods, the study develops an AI customer analysis technique applied to the RSC clustering analysis method for improving and sustaining military personnel fitness.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.97-102
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• 2023

This study is to provide improvement of tester for IoT system, which has recently become diversified and large-scale and It is about a method to improve the packet processing performance of the tester and securing flexibility in traffic protocol creation and operation. The purpose of this study is to design a OSS DPDK-based high-speed IoT network performance test system, which pre-verifies and measures the performance of data traffic transmission in an increasingly sophisticated high-capacity IoT network system. The basic structure of the high-speed IoT performance tester was designed using a DPDK-based traffic generator, the expected effect was suggested to traffic modeling and packet generation capability when the system was applied through experiments

• The Journal of the Acoustical Society of Korea
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• v.26 no.6
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• pp.259-268
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• 2007

This paper contributes to an improvement of the statistical bandwidth extension(BWE) system based on Hidden Markov Model(HMM). First, the existing HMM training method for BWE, which is suggested originally by Jax, is analyzed in comparison with the general Baum-Welch training method. Next, based on this analysis, a new HMM-based BWE method is suggested which adopts the Baum-Welch re-estimation algorithm instead of the Jax's to train HMM model. Conclusionally speaking, the Baum-Welch re-estimation algorithm is a generalized form of the Jax's training method. It is flexible and adaptive in modeling the statistical characteristic of training data. Therefore, it generates a better model to the training data, which results in an enhanced BWE system. According to experimental results, the new method performs much better than the Jax's BWE systemin all cases. Under the given test conditions, the RMS log spectral distortion(LSD) scores were improved ranged from 0.31dB to 0.8dB, and 0.52dB in average.

• The Journal of the Acoustical Society of Korea
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• v.27 no.3
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• pp.119-128
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• 2008

This paper analyzes the relationship between two representative statistical methods for bandwidth extension (BWE): Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM) ones, and compares their performances. The HMM method is a memory-based system which was developed to take advantage of the inter-frame dependency of speech signals. Therefore, it could be expected to estimate better the transitional information of the original spectra from frame to frame. To verify it, a dynamic measure that is an approximation of the 1st-order derivative of spectral function over time was introduced in addition to a static measure. The comparison result shows that the two methods are similar in the static measure, while, in the dynamic measure, the HMM method outperforms explicitly the GMM one. Moreover, this difference increases in proportion to the number of states of HMM model. This indicates that the HMM method would be more appropriate at least for the 'blind BWE' problem. On the other hand, nevertheless, the GMM method could be treated as a preferable alternative of the HMM one in some applications where the static performance and algorithm complexity are critical.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.4
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• pp.425-432
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• 2024

In this study, we propose a self-restoring friction slit damper by combining the concepts of self-restoring dampers, friction dampers, and steel dampers that are currently used and researched. For this purpose, an innovative damper structure was designed using superelastic shape memory alloy for automatic recovery and combining the concepts of friction damper and slit damper. Afterwards, detailed design was carried out and variables such as material, with of strut, and bolt fastening force were set. Modeling was performed using the ABAQUS program for a total of 12 dampers, and finite element analysis was performed by substituting the designed loading protocol. As a result, the self-recovering friction slit damper using superelastic shape memory alloy was excellent in terms of load, but the energy dissipation ability was not significantly secured due to the excellent recovery performance. However, friction slit dampers made of Gr.50 steel have dramatically improved performance in terms of load and energy dissipation through innovative structural improvements. Through this, the innovative structure of the damper, which combines the mechanisms of a friction damper and a steel damper, was demonstrated.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.181-186
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• 2003

The satellite navigation system is widely used for identifying a user's position regardless of weather or geographic conditions and also make effect on new technology of marine LBS(Location Based Service), which has the technology of geographic information such as the ENC. Generally, there are conceivable systems of marine LBS such as ECDIS, or ECS that use the ENC itself with powerful processor in installed type on ships bridge. Since the ENC is relatively heavy structure with dummy format for data transfer between different systems, we should reduce the ENC to small and compact size in order to use it in mobile platform. In this paper, we assumed that the mobile system like PDA, or Webpad can be used for small capability of mobile platform. However, the ENC should be updated periodically by update profile data produced by HO. If we would reduce the ENC without a consideration of update, we could not get newly updated data furthermore. As summary, we studied considerations for ENC reduction with update capability. It will make the ENC be useful in many mobile platforms for various applications.

• Journal of Environmental Impact Assessment
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• v.24 no.5
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• pp.456-471
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• 2015

Emission source term is one of the strong controlling factors for the air quality simulation capability, particularly over the urban area. Ulsan is an industrial area and frequently required to simulate for environmental assessment. In this study, two CAPSS (Clean Air Policy Support System) emission data; CAPSS-2003 and CAPSS-2010 in Ulsan, were employed as an input data for WRF-CMAQ air quality model for emission assessment. The simulated results were compared with observations for the local emission dominant synoptic conditions which had negative vorticities and lower geostrophic wind speed at 850hPa weather maps. The measurements of CO, $NO_2$, $SO_2$ and $PM_{10}$ concentrations were compared with simulations and the 'scaling factors' of emissions for CO, $NO_2$, $SO_2$, and $PM_{10}$ were suggested in in aggregative and quantitative manner. The results showed that CAPSS-2003 showed no critical discrepancies of CO and $NO_2$ observations with simulations, while $SO_2$ was overestimated by a factor of more than 12, while $PM_{10}$ was underestimated by a factor of more than 20 times. However, CAPSS-2010 case showed that $SO_2$ and $PM_{10}$ emission were much more improved than CAPSS-2003. However, $SO_2$ was still overestimated by a factor of more than 2, and $PM_{10}$ underestimated by a factor of 5, while there was no significant improvement for CO and $NO_2$ emission. The estimated factors identified in this study can be used as'scaling factors'for optimizing the emissions of air pollutants, particularly $SO_2$ and $PM_{10}$ for the realistic air quality simulation in Ulsan.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.725-733
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• 2019

Sand dams are structures that can be used as auxiliary water resources in case of drought as sand accumulates due to barriers crossing valley rivers and valley water is stored in the voids, increasing the water level. This structure, which is mainly used in arid regions such as Africa, has not been installed in Korea. In Korea, there are only a few cases where water is taken from debris barriers that prevent debris flow. The purpose of this study is to evaluate the effect of water supply when the sand dam is installed downstream of the existing intake barrier in Seosang-ri valley, Chuncheon. For this purpose, modeling was performed by linking the basin hydrologic model and reservoir routing model. Changes in the water level, storage and discharge in the sand dam reservoir according to the size and intake of the sand dam are presented on a case-by-case basis. As a result of application, it was found that the water supply capacity due to the sand dam installation was improved at 95% reliability. Especially, when the size is L × B × H_o = 25 m × 15 m × 1 m and the pumping rates from intake barrier and sand dam are (Q₁, Q₂) = (30, 20), (35, 15) ㎥/day, the efficiency was the best for water supply of 50 ㎥/day.

• Journal of Satellite, Information and Communications
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• v.12 no.3
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• pp.80-85
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• 2017

In this paper, a mircrowave breakdown of X-band circular waveguide cavity filter, which occurred during ground test, was introduced, and electro-magnetic field simulation results to identify a root cause, and the analysis of possibility of its occurrence on orbit operation were presented. Filter modeling for simulation was conducted with a commercial tool (FEST3D), and electric fields inside the filter were monitored at the input of 1 W continuous wave. In our observation, strong electric field intensities were monitored on the tuning screws especially at the input of band-edge frequencies. The threshold power levels for the breakdown were also estimated and compared with the input power levels actually injected to the filter. From this estimation, we could figure out that the power exceeding the breakdown threshold was injected to the filter so that strong electric fields were generated and temperature increased high, and this became a root cause of the electrical short. Our further analysis showed that this kind of microwave breakdown is not likely to occur on orbit operation, and multipactor is expected not to occur at the input of band-edge frequencies. As a measure to prevent the microwave breakdown, we suggested to avoid the injection of band-edge frequencies and inject lower power levels to the filter.