• ETRI Journal
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• v.23 no.1
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• pp.16-22
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• 2001

Efficient quantization methods of the line spectrum pairs (LSP) which have good performances, low complexity and memory are proposed. The adaptive quantization range method utilizing the ordering property of LSP parameters is used in a scalar quantizer and a vector-scalar hybrid quantizer. As the maximum quantization range of each LSP parameter is varied adaptively on the quantized value of the previous order's LSP parameter, efficient quantization methods can be obtained. The proposed scalar quantization algorithm needs 31 bits/frame, which is 3 bits less per frame than in the conventional scalar quantization method with interframe prediction to maintain the transparent quality of speech. The improved vector-scalar quantizer achieves an average spectral distortion of 1 dB using 26 bits/frame. The performances of proposed quantization methods are also evaluated in the transmission errors.

• Korean Journal of Radiology
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• v.22 no.5
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• pp.697-705
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• 2021

Objective: To investigate the feasibility and the accuracy of the coronary CT angiography (CCTA)-derived Registry of Crossboss and Hybrid procedures in France, the Netherlands, Belgium and United Kingdom (RECHARGE) score (RECHARGECCTA) for the prediction of procedural success and 30-minutes guidewire crossing in percutaneous coronary intervention (PCI) for chronic total occlusion (CTO). Materials and Methods: One hundred and twenty-four consecutive patients (mean age, 54 years; 79% male) with 131 CTO lesions who underwent CCTA before catheter angiography (CA) with CTO-PCI were retrospectively enrolled in this study. The RECHARGECCTA scores were calculated and compared with RECHARGECA and other CTA-based prediction scores, including Multicenter CTO Registry of Japan (J-CTO), CT Registry of CTO Revascularisation (CT-RECTOR), and Korean Multicenter CTO CT Registry (KCCT) scores. Results: The procedural success rate of the CTO-PCI procedures was 72%, and 61% of cases achieved the 30-minutes wire crossing. No significant difference was observed between the RECHARGECCTA score and the RECHARGECA score for procedural success (median 2 vs. median 2, p = 0.084). However, the RECHARGECCTA score was higher than the RECHARGECA score for the 30-minutes wire crossing (median 2 vs. median 1.5, p = 0.001). The areas under the curve (AUCs) of the RECHARGECCTA and RECHARGECA scores for predicting procedural success showed no statistical significance (0.718 vs. 0.757, p = 0.655). The sensitivity, specificity, positive predictive value, and the negative predictive value of the RECHARGECCTA scores of ≤ 2 for predictive procedural success were 78%, 60%, 43%, and 87%, respectively. The RECHARGECCTA score showed a discriminative performance that was comparable to those of the other CTA-based prediction scores (AUC = 0.718 vs. 0.665-0.717, all p > 0.05). Conclusion: The non-invasive RECHARGECCTA score performs better than the invasive determination for the prediction of the 30-minutes wire crossing of CTO-PCI. However, the RECHARGECCTA score may not replace other CTA-based prediction scores for predicting CTO-PCI success.

• Journal of Soil and Groundwater Environment
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• v.20 no.3
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• pp.74-82
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• 2015

A method to filter out the effect of river stage fluctuations on groundwater level was designed using an artificial neural network-based time series model of groundwater level prediction. The designed method was applied to daily groundwater level data near the Gangjeong-Koryeong Barrage in the Nakdong river. Direct prediction time series models were successfully developed for both cases of before and after the barrage construction using past measurement data of rainfall, river stage, and groundwater level as inputs. The correlation coefficient values between observed and predicted data were over 0.97. Using the time series models the effect of river stage on groundwater level data was filtered out by setting a constant value for river stage inputs. The filtered data were applied to the hybrid water table fluctuation method in order to estimate the groundwater recharge. The calculated ratios of groundwater recharge to precipitation before and after the barrage construction were 11.0% and 4.3%, respectively. It is expected that the proposed method can be a useful tool for groundwater level prediction and recharge estimation in the riverside area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.736-742
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• 2003

This paper presents the propagation path loss in a tunnel which is a kinds of underground environments. To predict propagation path loss more accurately, we choose a straight tunnel with rectangular cross-section. The simulated receiver powers that are using a hybrid waveguide model and a Ray-Tracing method, are compared with the measured ones as a function of distance between TX and RX antennas in tunnel. The attenuation value of regression analysis for measured power in the tunnel is 0.0238dB/m which is similar to the one of the EH1.2 mode, 0.0246dB/m in hybrid waveguide model. By comparing simulation with measurement in tunnels, it has been shown that the measured values are approximate to the simulated results of ray-tracing model. In the analysis of wide-band channel characteristics of the tunnel, the more the distance between TX and RX antennas in tunnel increases, RMS delay spread increases and coherence bandwidth decreases.

• KEPCO Journal on Electric Power and Energy
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• v.1 no.1
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• pp.33-38
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• 2015

Energy storage systems (ESSs) have been utilized widely in the world to optimize the power operation system and to improve the power quality. As lithium secondary batteries are the main power supplier for ESSs, it is very important to predict its cycle and power degradation behavior. In particular, the power, one of the hardest electrochemical properties to measure, needs lots of resources such as time and facilities. Due to these difficulties, computer modelling of lithium secondary batteries is applied to predict the DC-IR and power value during charging and discharging as a function of state of charge (SOC) by using pulse-based measurement methods. Moreover, based on the hybrid pulse power characteristics (HPPC) and J-Pulse (JEVS D 713, Japan Electric Vehicle Association Standards) methods, their electrochemical properties are also compared and discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.10
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• pp.2966-2983
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• 2024

Considering the intricate and ever-changing nature of the marine environment and the diverse range of sizes for targets involved in marine ship target recognition, which present challenges in detecting specific targets, a marine ship target detection algorithm has been developed based on an enhanced iteration of YOLOv5. Initially, the integration of dynamic snake convolution (DySnakeConv) into the feature extraction network and subsequent enhancement of the C3 module based on this integration were implemented. This integration enables dynamic adjustments based on the input image size, adaptive fusion of feature sequences, and resolution of accuracy and continuity issues during the recognition process. Subsequently, a novel hybrid encoder (FSI) was devised, utilizing target scale characteristics to enhance the extraction capability of multi-scale information, facilitating effective detection and recognition of objects within images. Finally, we selected the Shape-IOU bounding box loss function to mitigate fixed target frame issues and enhance target detection accuracy. Experimental evaluations were conducted utilizing the Infrared Maritime Ship dataset. The results demonstrated that our enhanced model achieved a prediction accuracy of 93.8% and an average precision (mAP) value of 93.89%, surpassing YOLOv8s by 1.2% and 1.8%, respectively. Moreover, there was an increase in recall rate by 2% compared to YOLOv8n while reducing parameters from 10,473,392 to 6,549,901 only. The computational load decreased by 6.3 GFLOps compared with YOLOV8n, resulting in better performance in ocean target detection and recognition.

• 한국전산유체공학회:학술대회논문집
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• 2008.03a
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• pp.104-110
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• 2008

Detached Eddy Simulation (DES) is applied to an axisymmetric base flow at supersonic mainstream. DES is a hybrid approach to modeling turbulence that combines the best features of the Reynolds-averaged Navier-Stokes RANS) and large-eddy simulation (LES) approaches. In the Reynolds-averaged mode, the model is currently based on either the Spalart-Allmaras (S-A) turbulence model. In the large eddy simulation mode, it is based on the Smagorinski subgrid scale model. Accurate predictions of the base flowfield and base pressure are successfully achieved by using the DES methodology with less computational cost than that of pure LES and monotone integrated large-eddy simulation (MILES) approaches. The DES accurately resolves the physics of unsteady turbulent motions, such as shear layer rollup, large-eddy motions in the downstream region, small-eddy motions inside the recirculating region. Comparison of the results shows that it is necessary to resolve approaching boundary layers and free shear-layer velocity profiles from the base edge correctly for the accurate prediction of base flows. The consideration of an empirical constant CDES for a compressible flow analysis may suggest that the optimal value of empirical constant CDES may be larger in the flows with strong compressibility than in incompressible flows.

• 한국전산유체공학회:학술대회논문집
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• 2008.10a
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• pp.104-110
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• 2008

Detached Eddy Simulation (DES) is applied to an axisymmetric base flow at supersonic mainstream. DES is a hybrid approach to modeling turbulence that combines the best features of the Reynolds-averaged Navier-Stokes (RANS) and large-eddy simulation (LES) approaches. In the Reynolds-averaged mode, the model is currently based on either the Spalart-Allmaras (S-A) turbulence model. In the large eddy simulation mode, it is based on the Smagorinski subgrid scale model. Accurate predictions of the base flowfield and base pressure are successfully achieved by using the DES methodology with less computational cost than that of pure LES and monotone integrated large-eddy simulation (MILES) approaches. The DES accurately resolves the physics of unsteady turbulent motions, such as shear layer rollup, large-eddy motions in the downstream region, small-eddy motions inside the recirculating region. Comparison of the results shows that it is necessary to resolve approaching boundary layers and free shear-layer velocity profiles from the base edge correctly for the accurate prediction of base flows. The consideration of an empirical constant CDES for a compressible flow analysis may suggest that the optimal value of empirical constant CDES may be larger in the flows with strong compressibility than in incompressible flows.

• Journal of the Korean Magnetics Society
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• v.26 no.3
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• pp.81-85
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• 2016

This paper introduces a performance integration method to predict variation characteristic of a performance function of electromagnetic machines or devices due to manufacturing tolerances. A normalized performance function space and a hybrid mean value technique are adapted to effectively predict mean and variance, which can identify probabilistic distribution of the performance function. To verify the effectiveness and accuracy of the proposed method, a mathematical problem and a loudspeaker model are tested, and numerical results are compared with those of existing methods such as Monte Carlo simulation and univariate dimension reduction method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5392-5418
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• 2017

The primary aim of this paper is to propose a non-linear regression based technique for mapping different network Quality of Service (QoS) factors to an integrated end-user Quality of Experience (QoE) or Mean Opinion Score (MOS) value for an online video streaming service on a mobile phone. We use six network QoS factors for finding out the user QoE. The contribution of this paper is threefold. First, we investigate the impact of the network QoS factors on the perceived video quality. Next, we perform an individual mapping of the significant network QoS parameters obtained in stage 1 to the user QoE based upon a non-linear regression method. The optimal QoS to QoE mapping function is chosen based upon a decision variable. In the final stage, we evaluate the integrated QoE of the system by taking the combined effect of all the QoS factors considered. Extensive subjective tests comprising of over 50 people across a wide variety of video contents encoded with H.265/HEVC and VP9 codec have been conducted in order to gather the actual MOS data for the purpose of QoS to QoE mapping. Our proposed hybrid model has been validated against unseen data and reveals good prediction accuracy.