• Journal of the Korea Safety Management & Science
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• v.21 no.2
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• pp.15-23
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• 2019

Among service industries of knowledge based economic era, the roles of educational service field are becoming more important and standard of educational service makes a direct effect on economic development and social growth. Therefore, accurate measurement of service quality is the most important assignment and the measurement of the service quality remains difficult assignment. So, this researcher classified quality attributes applying weighted value and found potential satisfaction level(PSL) and potential customer demand improvement index(PCDI) for trainees participating in national manpower business so as to suggest measurement of service quality and easiness of use and then, calculated satisfaction position and opportunity cost by quality factor with Taguchi's loss fraction. And, improvable satisfaction level was measured, opportunity cost by degree of customer dissatisfaction was quantitatively measured, and a model that can indicate with economic factors was suggested. In addition, methodology of measuring quality cost that can be reduced by quality improvement and direction of strategic decision-making for deciding items to be improved preferentially were suggested with qualitative index that can indicate the degree of customers' dissatisfaction by loss.

• The KSFM Journal of Fluid Machinery
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• v.14 no.1
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• pp.66-76
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• 2011

The heat transfer and pressure loss characteristics of a rotating two-pass channel with a guide vane in the turning region have been studied using three-dimensional Reynolds-averaged Navier-Stokes (RANS) analysis, and the shape of the guide vane has been optimized using surrogate modeling optimization technique. For the optimization, thickness, location and angle of the guide vanes have been selected as design variables. The objective function has been defined as a linear combination of the heat transfer and the friction loss related terms with a weighting factor. Latin hypercube sampling has been applied to determine the design points as design of experiments. A weighted-average surrogate model, PBA has been used as the surrogate model. The guide vane in the turning region does not influence the heat transfer in the first passage upstream of the turning region, but enhances largely the heat transfer in the turning region and the second passage. In an example of the optimization, the objective function has been increased by 13.6%.

• Journal of the Korea Safety Management & Science
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• v.21 no.1
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• pp.9-16
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• 2019

Logistics companies are worrying about securing of differential competitiveness so as to be competitive companies in keen logistics market. The ground is how users are satisfied by sell-established service system to respond not only economic feasibility of logistics costs but also diversity and advancement of logistics needs. The competitiveness of logistics companies is also caused by customer satisfaction of service and only companies finding and satisfying customer needs continuously may be more competitive. For the competitiveness, it's the most important to analyze demands of current and potential customers and their pursuing value properly. Therefore, this researcher grasped PSL for online logistics service users with 5-point Likert-scale and quality-level decision method that consider the weighted value based on Kano model, measured customer's potential Demand for service through PCDI, and suggested methodology for deciding the priority of the improvement with loss function of Taguchi.

• The Journal of the Acoustical Society of Korea
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• v.18 no.1
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• pp.10-15
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• 1999

We have studied a method to design and fabricate the Intermediate Frequency(IF) band pass filter with low shape factor which is used for CDMA base station on the 35°Y-cut X-propagation Quartz substrate. In order to fabricate a device of the low shape factor for the IF SAW filter on this substrate, we employed apodization weighted type interdigital transducer(IDT) as an input and withdrawal weighted type IDT as an output by using impulse modelling method. Also, using the Kaiser-Bessel window function, we have adopted 2200pairs and 1000pairs of input and oueut IDT respectively to minimize the effect of ripple. Furthermore, the width and the space of IDT finger are 3.6 ㎛ and 3.5 ㎛ respectively. Thus, we can have optimal results when the IDT thickness is 6000Å in consideration of the ratio of SAW's wavelength while it's aperture is 2mm for impedance matching. The fabricated SAW filter for CDMA had the property of almost 115.2MHz of a center frequency, less then 1.27MHz of bandwidth, less than 1.3 of shape factor, - l5dB of out band attenuation insertion loss and -45dB of rejection band.

• Journal of Navigation and Port Research
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• v.44 no.5
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• pp.423-429
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• 2020

A ship's automatic steering system is the basis for addressing control difficulties related to course-changing and course-keeping during navigation through heading angle control, and is a link in realizing unmanned and autonomous ships. This study proposes a robust RCGA-based linear active disturbance rejection controller (LADRC) design method considering environmental disturbances, measurement noise, and model uncertainties in designing a ship heading controller for use when the ship is sailing. The LADRC consisted of a transient profile, a linear extended state observer, and a PD controller. The control gains in the LADRC with the linear extended state observer were adjusted by RCGAs to minimize the integral of the time-weighted absolute error (ITAE), which is an evaluation function of the control system. The proposed method was applied to ship heading control, and its effectiveness was validated by comparing the propulsive energy loss between the proposed method and a conventional linear PD controller. The simulation results showed that the proposed method had the advantages of lower propulsive energy loss, more robustness, and higher tracking precision than the conventional linear PD controller.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.300-312
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• 2021

Compressed sensing (CS) has been investigated in magnetic resonance (MR) parametric mapping to reduce scan time. However, the relatively long reconstruction time restricts its widespread applications in the clinic. Recently, deep learning-based methods have shown great potential in accelerating reconstruction time and improving imaging quality in fast MR imaging, although their adaptation to parametric mapping is still in an early stage. In this paper, we proposed a novel deep learning-based framework DEMO for fast and robust MR parametric mapping. Different from current deep learning-based methods, DEMO trains the network in an unsupervised way, which is more practical given that it is difficult to acquire large fully sampled training data of parametric-weighted images. Specifically, a CS-based loss function is used in DEMO to avoid the necessity of using fully sampled k-space data as the label, thus making it an unsupervised learning approach. DEMO reconstructs parametric weighted images and generates a parametric map simultaneously by unrolling an interaction approach in conventional fast MR parametric mapping, which enables multi-tasking learning. Experimental results showed promising performance of the proposed DEMO framework in quantitative MR T1ρ mapping.

• Smart Structures and Systems
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• v.31 no.4
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• pp.335-349
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• 2023

Bridges constantly undergo deterioration and damage, the most common ones being concrete damage and exposed rebar. Periodic inspection of bridges to identify damages can aid in their quick remediation. Likewise, identifying components can provide context for damage assessment and help gauge a bridge's state of interaction with its surroundings. Current inspection techniques rely on manual site visits, which can be time-consuming and costly. More recently, robotic inspection assisted by autonomous data analytics based on Computer Vision (CV) and Artificial Intelligence (AI) has been viewed as a suitable alternative to manual inspection because of its efficiency and accuracy. To aid research in this avenue, this study performs a comparative assessment of different architectures, loss functions, and ensembling strategies for the autonomous segmentation of bridge components and damages. The experiments lead to several interesting discoveries. Nested Reg-UNet architecture is found to outperform five other state-of-the-art architectures in both damage and component segmentation tasks. The architecture is built by combining a Nested UNet style dense configuration with a pretrained RegNet encoder. In terms of the mean Intersection over Union (mIoU) metric, the Nested Reg-UNet architecture provides an improvement of 2.86% on the damage segmentation task and 1.66% on the component segmentation task compared to the state-of-the-art UNet architecture. Furthermore, it is demonstrated that incorporating the Lovasz-Softmax loss function to counter class imbalance can boost performance by 3.44% in the component segmentation task over the most employed alternative, weighted Cross Entropy (wCE). Finally, weighted softmax ensembling is found to be quite effective when used synchronously with the Nested Reg-UNet architecture by providing mIoU improvement of 0.74% in the component segmentation task and 1.14% in the damage segmentation task over a single-architecture baseline. Overall, the best mIoU of 92.50% for the component segmentation task and 84.19% for the damage segmentation task validate the feasibility of these techniques for autonomous bridge component and damage segmentation using RGB images.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.237-242
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• 2005

Predicting the cellular location of an unknown protein gives a valuable information for inferring the possible function of the protein. For more accurate prediction system, we need a good feature extraction method that transforms the raw sequence data into the numerical feature vector, minimizing information loss. In this paper, we propose new methods of extracting underlying features only from the sequence data by computing pairwise sequence alignment scores. In addition, we use composition based features to improve prediction accuracy. To construct an SVM ensemble from separately trained SVM classifiers, we propose specificity based weighted majority voting. The overall prediction accuracy evaluated by the 5-fold cross-validation reached 88.53% for the eukaryotic animal data set. By comparing the prediction accuracy of various feature extraction methods, we could get the biological insight on the location of targeting information. Our numerical experiments confirm that our new feature extraction methods are very useful for predicting subcellular localization of proteins.

• Journal of Korean Society for Quality Management
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• v.27 no.2
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• pp.218-236
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• 1999

The purpose of parameter design is to determine optimal settings of design parameters of a product or a process such that the performance characteristics of a product exhibit small variabilities around their target values. Taguchi made significant contributions in this area. However, his analysis of the problem focused on only one performance characteristic or response, although in product and process design, multiple characteristics are more common. The critical problem in dealing with multiple characteristics is how to compromise the conflict among the selected levels of the design parameters for each individual characteristic. In this paper, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal balance among several different response variables is developed. Existing case studies are solved by the proposed method and the results are compared with ones by the sum of SN ratios, the expected weighted loss, the desirability function, and EXTOPSIS model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.171-181
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• 1999

Taguchi's robust design methodology has focus only a single characteristic or response, but the quality of most products is seldom defined by a characteristics, and is rather the composite of a family of characteristics which are often interrelated and nearly always measured in a variety of units. The multiple characteristics problem is how to compromise the conflicts among the selected levels of the design parameters for each individual characteristic. In this paper, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achive the optimal compromise among several different response variables is developed. One new case studies are solved by the proposed method and the results are compared with ones by the sum of SN ratios, the expected weighted loss, the desirability function, and EXTOPSIS model.