• Journal of the Korean Society of Safety
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• v.24 no.3
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• pp.19-24
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• 2009

Currently the technique of composite material field is developed day by day. The many kinds industrial facility and life articles are coming to make with the composite material. But still the engineering works field the building and the bridge uses the material which is old era and is making. To here there is a various problem but the biggest problem the theory of the composite material is complicated too and means that the application is been delayed about constructive structure. When the composite material is used widely from constructive field, too with difficult theory in technical expert and easily with the research for the experiment data accumulation is necessary. The tensile and fatigue test of the carbon/epoxy which is a high-class composite material led from the present paper consequently and the change of the intensity coefficient which follows in repeated load researched.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.376-376
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• 2000

Several algorithmic models have been proposed to estimate software cost and other management parameters. In particular, early prediction of completion time is absolutely essential for proper advance planning and a version of the possible ruin of a project. However, estimation is difficult because of its similarity to export judgment approaches and for its potential as an expert assistant in support of human judgment. Especially, the nature of the Norden/Rayleigh curve used by Putnam, renders it unreliable during the initial phases of the project, in projects involving a fast manpower buildup, as is the case with most software projects. Estimating software development effort is more complexity, because of infrastructure software related to target-machines hardware and process characteristics should be considered in software development for DCS (Distributed Control System). In this paper, we propose software development effort estimation technique using adaptive neural fuzzy inference system. The methods is applied to case-based projects and discussed.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1489-1502
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• 2019

This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2395-2397
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• 2000

In this paper, a new method for color measuring is presented using fuzzy modeling technique. The fuzzy and polynomial inferences are used for obtaining RGB characteristic curve. The eight RGB real data from expert dye-stuff manufacturer, are simulated. The results show that the proposed method is more excellent than other methods, in the color measuring process of textile field.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.6
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• pp.110-116
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• 1994

In this research, the tensile strength of molded parts and pressure distribution were analyzed to study the cavity filling stage and packing stage in injection molding. The measurement of cavity pressure was obtained by a data acquisition system with the installation of transducers in the cavity. Molded parts were tested by a universal testing machine to obtain the tensile strength. For the experimental work, the tensile strength of molded parts increased with longer packing time and exact freezing time of the gate was obtained by a cavity pressure curve. In addition, the effect of packing did not occur and tensile strength was almost constant after early 1.5 sec of the freezing time of gate. Density tended to be higher about 0.2% due to a larger degree of mold temperature and melt temperature. Also, changing pressure in the cavity was effectively sensed. Thereafter, the possibility of the development of pattern recognition expert system was confirmed on the basis of the experimental results.

• Journal of Chest Surgery
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• v.48 no.2
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• pp.105-111
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• 2015

Background: The aim of this study was to establish whether pulmonary lobectomy using video-assisted thoracic surgery (VATS) can be safely performed by trainees with limited experience with open lobectomy. Methods: Data were retrospectively collected from 251 patients who underwent VATS lobectomy at a single institution between October 2007 and April 2011. The surgical outcomes of the procedures that were performed by three trainee surgeons were compared to the outcomes of procedures performed by a surgeon who had performed more than 150 VATS lobectomies. The cumulative failure graph of each trainee was used for quality assessment and learning curve analysis. Results: The surgery time, estimated blood loss, final pathologic stage, thoracotomy conversion rate, chest tube duration, duration of hospital stay, complication rate, and mortality rate were comparable between the expert surgeon and each trainee. Cumulative failure graphs showed that the performance of each trainee was acceptable and that all trainees reached proficiency in performing VATS lobectomy after 40 cases. Conclusion: This study shows that trainees with limited experience with open lobectomy can safely learn to perform VATS lobectomy for the treatment of lung cancer under expert supervision without compromising outcomes.

• Advances in aircraft and spacecraft science
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• v.5 no.4
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• pp.499-513
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• 2018

One of the major problems in glass fiber reinforced epoxy (GFRE) composite pipes is the durability under water absorption. This condition is generally recognized to cause degradations in strength and mechanical properties. Therefore, there is a need for an intelligent system for detecting the absorption rate and computing the mass of water absorption (M%) as a function of absorption time (t). The present work represents a new non-destructive evaluation (NDE) technique for detecting the water absorption rate by evaluating the dielectric properties of glass fiber and epoxy resin composite pipes subjected to internal hydrostatic pressure at room temperature. The variation in the dielectric signatures is employed to design an electrical capacitance sensor (ECS) with high sensitivity to detect such defects. ECS consists of twelve electrodes mounted on the outer surface of the pipe. Radius-electrode ratio is defined as the ratio of inner and outer radius of pipe. A finite element (FE) simulation model is developed to measure the capacitance values and node potential distribution of ECS electrodes on the basis of water absorption rate in the pipe material as a function of absorption time. The arrangements for positioning12-electrode sensor parameters such as capacitance, capacitance change and change rate of capacitance are analyzed by ANSYS and MATLAB to plot the mass of water absorption curve against absorption time (t). An analytical model based on a Fickian diffusion model is conducted to predict the saturation level of water absorption ($M_S$) from the obtained mass of water absorption curve. The FE results are in excellent agreement with the analytical results and experimental results available in the literature, thus, validating the accuracy and reliability of the proposed expert system.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.21 no.2
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• pp.118-126
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• 2018

Purpose: Classical criteria for diagnosis of autoimmune hepatitis (AIH) are intended as research tool and are difficult to apply at patient's bedside. We aimed to study the accuracy of simplified criteria and the concordance with the expert diagnosis based on the original criteria. Methods: A cohort of children under study for liver disorder was selected through consecutive sampling to obtain the prevalence of AIH within the group of differential diagnoses. AIH was defined, based on classical criteria, through committee review of medical reports. Validity indicators of the simplified criteria were obtained in an intention to diagnose approach. Optimal cut-off and the area under the receiver operating characteristic (ROC) curve were calculated. Results: Out of 212 cases reviewed, 47.2% were AIH. For the optimal cut-off (6 points), the simplified criteria showed a sensitivity of 72.0% and a specificity of 96.4%, with a 94.7% positive and a 79.4% negative predictive value. The area under the ROC curve was 94.3%. There was a good agreement in the pre-treatment concordance between the classical and the simplified criteria (kappa index, 0.775). Conclusion: Simplified criteria provide a moderate sensitivity for the diagnosis of AIH, but may help in indicating treatment in cases under suspicion with 6 or more points.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.205-211
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• 2020

The method of predicting the future may be predicted by technical characteristics or technical performance. Therefore, technology prediction is used in the field of strategic research that can produce economic and social benefits. In this study, we predicted the future market through the study of how to predict the future with these technical characteristics. The future prediction method was studied through the prediction of the time when the market occupied according to the demand of special product. For forecasting market demand, we proposed the future forecasting model through comparison of representative quantitative analysis methods such as CAGR model, BASS model, Logistic model and Gompertz Growth Curve. This study combines Rogers' theory of innovation diffusion to predict when products will spread to the market. As a result of the research, we developed a methodology to predict when a particular product will mature in the future market through the spread of various factors for the special product to occupy the market. However, there are limitations in reducing errors in expert judgment to predict the market.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.27 no.2
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• pp.83-90
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• 1997

This study was performed to demonstrate the effect of linear or nonlinear contrast enhancement on subtraction images. Three different textures were radiograped on dental film. The first radiograph was taken without the presence of an object. the second, which showed trabucular bone, was taken of the molar area of a human. the third radiograph was taken of the coronal part of molars. Each film was digitized into a 1312 x 1024 pixel x 8 bit depth matrix by means of a Nikon 35 mm film scanner(LS-3510AF, Japan) with fixed gain and internal dark current correction to maintain constant illumination. The scanner was interfaced to a Macintosh Le ill computer(Apple Computer, Charlotte, N.C) This resulted in three pairs of images, including different textures-plain, bone and enamel. Digital regular, linearly and nonlinearly enhanced subtraction was performed. Computer software was ,used to simulate lesions in the shape of a 2D-Gaussian curve on each of a pair of images. The each subtraction images were presented in a random sequence to two groups of 10 observers(students and dentists). ROC analysis was used to compare observer performance. The following results were obtained ; 1. All of LCE subtraction, equalized subtraction and regular subtraction images of plain texture were diagnosed the best by far. 2. The data revealed a siginificant LCE effect in both the student group and the expert group. 3. Clinical expertise was a helphul factor for the observers in this study.