• JSTS:Journal of Semiconductor Technology and Science
• /
• v.10 no.2
• /
• pp.134-142
• /
• 2010

A comparative study on the trade-off between the drive current and the total gate capacitance in double-gate (DG) and triple-gate (TG) FinFETs is performed by using 3-D device simulation. As the first result, we found that the optimum ratio of the hardmask oxide thickness ($T_{mask}$) to the sidewall oxide thickness ($T_{ox}$) is $T_{mask}/T_{ox}$=10/2 nm for the minimum logic delay ($\tau$) while $T_{mask}/T_{ox}$=5/1~2 nm for the maximum intrinsic gate capacitance coupling ratio (ICR) with the fixed channel length ($L_G$) and the fin width ($W_{fin}$) under the short channel effect criterion. It means that the TG FinFET is not under the optimal condition in terms of the circuit performance. Second, under optimized $T_{mask}/T_{ox}$, the propagation delay ($\tau$) decreases with the increasing fin height $H_{fin}$. It means that the FinFET-based logic circuit operation goes into the drive current-dominant regime rather than the input gate load capacitance-dominant regime as $H_{fin}$ increases. In the end, the sensitivity of $\Delta\tau/{\Delta}H_{fin}$ or ${{\Delta}I_{ON}}'/{\Delta}H_{fin}$ decreases as $L_G/W_{fin}$ is scaled-down. However, $W_{fin}$ should be carefully designed especially in circuits that are strongly influenced by the self-capacitance or a physical layout because the scaling of $W_{fin}$ is followed by the increase of the self-capacitance portion in the total load capacitance.

• Journal of the Korean Institute of Gas
• /
• v.19 no.5
• /
• pp.13-19
• /
• 2015

This paper presents a hydraulic fracture propagation model to describe propagation more realistically. In propagating the hydraulic fractures, we have used two criteria: maximum tangential stress to determine the fracture initiation angle and whether a hydraulic fracture intersects a natural fracture. The model was validated for the parameters relevant to fracture propagation, such as initiation angle and crossing ability through natural fracture. In order to check whether a hydraulic fracture crosses a natural fracture, the model results on crossing state excellently matched with the experimental data. In the sensitivity analysis for direction of maximum horizontal stress, frictional coefficient of fracture interface, and natural fracture orientation, the results show that hydraulic fracture intersects natural fracture, and then, propagated suitably with theoretical results according to fracture interaction criterion. In comparison of this model against vertical fracture approach, it was ascertained that there are discrepancies in fracture connectivity and stimulated reservoir volume.

• Journal of Physiology & Pathology in Korean Medicine
• /
• v.20 no.1
• /
• pp.235-244
• /
• 2006

There is much confusion in the field of Rhinitis regarding how to best measure disease severity objectively, Therefore, we aimed to establish a new adequate scoring system for Rhinitis, that should be based on comparison analysis of various scoring systems. We report as follows. We researched for data relating to severity scoring systems for rhinitis in Entrez PubMed from 1995 to 2005 and in Kiss Kstudy. Results and Conclusions: Properties of severity scoring systems were validity, sensitivity of change and ease of use. The essential items of severity scoring systems were subjective symptoms. The criterion of severity were divided into subjective symptoms and complication and Quality of Life. Intensity items are nasal obstruction, rhinorrhea, sneezing, itching, Postnasal drip, nasal mucosa swelling, nasal mucosa color, complication. Subjective symptoms is difficulty of Life. The significant items of severity scoring system are nasal symptoms. The whole score does with the maximum 30 scores. As it were, we assumed nasal symptoms accounted for around 80% of each total score, with complication and difficulty of Life representing 20%.

• Journal of the Society of Disaster Information
• /
• v.17 no.3
• /
• pp.427-441
• /
• 2021

Purpose: This study proposes a method for developing a model that predicts the probability of traffic accidents in advance to prevent the most frequent traffic accidents in the military. Method: For this purpose, CRISP-DM (Cross Industry Standard Process for Data Mining) was applied in this study. The CRISP-DM process consists of 6 stages, and each stage is not unidirectional like the Waterfall Model, but improves the level of completeness through feedback between stages. Results: As a result of modeling the same data set as the previously constructed accident investigation data for the entire group, when the classification criterion was 0.5, Significant results were derived from the accuracy, specificity, sensitivity, and AUC of the model for predicting traffic accidents. Conclusion: In the process of designing the prediction model, it was confirmed that it was difficult to obtain a meaningful prediction value due to the lack of data. The methodology for designing a predictive model using the data set was proposed by reorganizing and expanding a data set capable of rational inference to solve the data shortage.

• Computers and Concrete
• /
• v.23 no.3
• /
• pp.161-170
• /
• 2019

This paper aims at presenting a numerical method for estimating the elastic modulus of recycled concrete with crushed aggregates. In the method, polygonal aggregates following a given sieve curve are generated, and placed into a square simulation element with the aid of the periodic boundary condition and the overlap criterion of two polygonal aggregates. The mesostructure of recycled concrete is reconstructed by embedding an old interfacial transition zone (ITZ) layer inside each recycled aggregate and by coating all the aggregates with a new ITZ layer. The square simulation element is discretized into a regular grid and a representative point is selected from each sub-element. The iterative method is combined with the fast Fourier transform to evaluate the elastic modulus of recycled concrete. After the validity of the numerical method is verified with experimental results, a sensitivity analysis is conducted to evaluate the effects of key factors on the elastic modulus of recycled concrete. Numerical results show that the elastic modulus of recycled concrete increases with the increase of the total aggregate content and the elastic moduli of old and new ITZ but decreases with increasing the replacement ratio of recycled aggregate and the thicknesses of old and new ITZ. It is also shown that, for a replacement ratio of recycled aggregate smaller than 0.3, the elastic modulus of recycled concrete is reduced by no more than 10%.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.41 no.4
• /
• pp.238-247
• /
• 2018

This paper considers the problem of scheduling loading and unloading operations of a crane in a railway terminal motivated from rail-road container transshipment operations at Uiwang Inland Container Depot (ICD). Unlike previous studies only considering the total handling time of containers, this paper considers a bi-criteria objective of minimizing the weighted sum of the total handling time and tenant service time. The tenant service time is an important criterion in terms of terminal tenants who are private logistics companies in charge of moving containers from/to the terminal using their trucks. In the rail-road container shipment yard, the tenant service time of a tenant can be defined by a time difference between beginning and finishing loading and unloading operations of a crane. Thus, finding a set of sequences and time of the crane operations becomes a crucial decision issue in the problem. The problem is formulated as a nonlinear program which is improved by linearizing a nonlinear constraint in the model. This paper develops a genetic algorithm to solve the problem and performs a case study on the Uiwang ICD terminal. Computational experiment results show that the genetic algorithm shows better performance than commercial optimization solvers. Operational implications in terms of tenants are drawn through sensitivity analyses.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.41 no.4
• /
• pp.203-212
• /
• 2018

Quality requirements of manufactured products or parts are given in the form of specification limits on the quality characteristics of individual units. If a product is to meet the customer's fitness for use criteria, it should be produced by a process which is stable or repeatable. In other words, it must be capable of operating with little variability around the target value or nominal value of the product's quality characteristic. In order to maintain and improve product quality, we need to apply statistical process control techniques such as histogram, check sheet, Pareto chart, cause and effect diagram, or control charts. Among those techniques, the most important one is control charting. The cumulative sum (CUSUM) control charts have been used in statistical process control (SPC) in industries for monitoring process shifts and supporting online measurement. The objective of this research is to apply Taguchi's quality loss function concept to cost based CUSUM control chart design. In this study, a modified quality loss function was developed to reflect quality loss situation where general quadratic loss curve is not appropriate. This research also provided a methodology for the design of CUSUM charts using Taguchi quality loss function concept based on the minimum cost per hour criterion. The new model differs from previous models in that the model assumes that quality loss is incurred even in the incontrol period. This model was compared with other cost based CUSUM models by Wu and Goel, According to numerical sensitivity analysis, the proposed model results in longer average run length in in-control period compared to the other two models.

• Nutrition Research and Practice
• /
• v.13 no.3
• /
• pp.247-255
• /
• 2019

BACKGROUND/OBJECTIVES: Accurate, early identification of acutely malnourished children has the potential to reduce related child morbidity and mortality. The current World Health Organisation (WHO) guidelines classify non-oedematous acute malnutrition among children under five using Mid-Upper Arm Circumference (MUAC) or Weight-for-Height Z-score (WHZ). However, there is ongoing debate regarding the use of current MUAC cut-offs. This study investigates the diagnostic performance of MUAC to identify children aged 6-24 months with global (GAM) or severe acute malnutrition (SAM). SUBJECTS/METHODS: Cross-sectional, secondary data from a community sample of children aged 6-24 months in Niger were used for this study. Children with complete weight, height and MUAC data and without clinical oedema were included. Using WHO guidelines for GAM (WHZ < -2, MUAC < 12.5 cm) and SAM (WHZ < -3, MUAC < 11.5 cm), the sensitivity (Se), specificity (Sp), predictive values, Youden Index and Receiver Operating Characteristic (ROC) curves were calculated for MUAC when compared with the WHZ reference criterion. RESULTS: Of 1161 children, 23.3% were diagnosed with GAM using WHZ, and 4.4% with SAM. Using current WHO cut-offs, the Se of MUAC to identify GAM was greater than for SAM (79 vs. 57%), yet the Sp was lower (84 vs. 97%). From inspection of the ROC curve and Youden Index, Se and Sp were maximised for MUAC < 12.5 cm to identify GAM (Se 79%, Sp 84%), and MUAC < 12.0 cm to identify SAM (Se 88%, Sp 81%). CONCLUSIONS: The current MUAC cut-off to identify GAM should continue to be used, but when screening for SAM, a higher cut-off could improve case identification. Community screening for SAM could use MUAC < 12.0 cm followed by appropriate treatment based on either MUAC < 11.5 cm or WHZ < -3, as in current practice. While the practicalities of implementation must be considered, the higher SAM MUAC cut-off would maximise early case-finding of high-risk acutely malnourished children.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.2
• /
• pp.714-720
• /
• 2021

The ITL (information theoretic learning) based on the kernel density estimation method that has successfully been applied to machine learning and signal processing applications has a drawback of severe sensitiveness in choosing proper kernel sizes. For the maximization of correntropy criterion (MCC) as one of the ITL-type criteria, several methods of adapting the remaining kernel size ( ) after removing the term have been studied. In this paper, it is shown that the main cause of sensitivity in choosing the kernel size derives from the term and that the adaptive adjustment of in the remaining terms leads to approach the absolute value of error, which prevents the weight adjustment from continuing. Thus, it is proposed that choosing an appropriate constant as the kernel size for the remaining terms is more effective. In addition, the experiment results when compared to the conventional algorithm show that the proposed method enhances learning performance by about 2dB of steady state MSE with the same convergence rate. In an experiment for channel models, the proposed method enhances performance by 4 dB so that the proposed method is more suitable for more complex or inferior conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.1
• /
• pp.16-37
• /
• 2022

Accurate liver segment segmentation based on radiological images is indispensable for the preoperative analysis of liver tumor resection surgery. However, most of the existing segmentation methods are not feasible to be used directly for this task due to the challenge of exact edge prediction with some tiny and slender vessels as its clinical segmentation criterion. To address this problem, we propose a novel deep learning based segmentation model, called Boundary-Aware Dual Attention Liver Segment Segmentation Model (BADA). This model can improve the segmentation accuracy of liver segments with enhancing the edges including the vessels serving as segment boundaries. In our model, the dual gated attention is proposed, which composes of a spatial attention module and a semantic attention module. The spatial attention module enhances the weights of key edge regions by concerning about the salient intensity changes, while the semantic attention amplifies the contribution of filters that can extract more discriminative feature information by weighting the significant convolution channels. Simultaneously, we build a dataset of liver segments including 59 clinic cases with dynamically contrast enhanced MRI(Magnetic Resonance Imaging) of portal vein stage, which annotated by several professional radiologists. Comparing with several state-of-the-art methods and baseline segmentation methods, we achieve the best results on this clinic liver segment segmentation dataset, where Mean Dice, Mean Sensitivity and Mean Positive Predicted Value reach 89.01%, 87.71% and 90.67%, respectively.