• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.6
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• pp.498-507
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• 2017

Electronic equipments comprised of high density components with various packaging types have been recently applied to a satellite. Therefore, to guarantee high reliability of electrical equipment, a design approach, which can reduce the development period and cost through an early diagnosis in potential risks of failure, should be established. In the previous research, the reliability assesment of the electronic equipments have based on Steinberg's fatigue failure theory. However, this theory was not enough for further investigation of life prediction and reliability of the electronic equipments comprised of various sizes and packaging types due to its theoretical limitations and analysis results sensitivity with regard to different modeling technic. In that case, if detailed finite element model is established, aforementioned problems can be readily solved. However, this approach might arise disadvantage of spending much time. In this paper, to establish strategy for high reliability design of electronic equipment, we performed mechanical reliability evaluation of CCB (Camera Controller Box) at qualification level based on the approach using Sherlock unlike design techniques applied to existing business.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.30 no.5
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• pp.414-421
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• 2004

This is a reprospective study on the care of odontogenic infections in admission patients with geriatric diseases. The study was based on a series of 480 patients at Dong San Medical Center, Wonju Christian Hospital and Il San Health Insurance Hospital, From Jan. 1, 2000, to Dec. 31, 2002. The Obtained results were as follows: 1. The systemic malignant tumor was the most frequent cause of the geriatric diseases with odontogenic infectious diseases, and refractory lung disease, systemic heart disease, type II diabetes mellitus, cerebrovascular disease, bone & joint disease, senile psychologic disease were next in order of frequency. 2. Male prediction(57.5%) was existed in the odontogenic infectious patients with geriatric diseases. But, there were female prediction in senile psychologic disease, systemic heart disease and cerebrovascular disease. 3. The most common age group of the odontogenic infectious patient with geriatric disease was the sixty decade(47.9%), followed by the seventy & eighty decade in order. 4. In the contents of chief complaints on the odontogenic infectious patients with geriatric disease, peak incidence was occurred as toothache(52.7%), followed by extraction wish, tooth mobility, oral bleeding, oral ulcer, fracture of restoration, gingival swelling in order. 5. In the diagnosis group of odontogenic infectious diseases, periodontitis, pulpitis & periapical abscess were more common. 6. In the treatment group of odontogenic infectious diseases, the most frequent incidence(34.2%) was showed in primary endodontic treatment (pulp extirpation, occlusal reduction and canal opening drainage) and followed by scaling, incision & drainage, only drugs, pulp capping, restoration in order.

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.4
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• pp.327-343
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• 2004

During tunnel construction, ground failures often occur due to existence of weak zones, such as faults, joints, and cavities, ahead of tunnel face. It is hard to detect effectively weak zones, which can lead underground structure to fail after excavation and before supporting, by using conventional characterization methods. In this study, an enhanced analytical method of predicting weak zones ahead of tunnel face is developed to overcome some problems in the conventional geophysical exploration methods. The analytical method is based on Coulomb's and Gauss' laws with considering the characteristics of electric fields subjected to rock mass. Using the developed method, closed form solutions are obtained to detect a spherical shaped zone and an oriented fault ahead of tunnel face respectively. The analytical results suggest that the presence of weak zones and their sizes, location, and states can be accurately predicted by combining a proper inversion process with resistance measured from several electrodes on the tunnel face. It appears that the skin depth or resistivity in rock mass is affected by the diameter of tunnel face, natural electric potential and noises induced by experimental measurement and spatial distribution of uncertain properties. The developed analytical solution is verified through experimental tests. About 1800 concrete blocks of 5cm by 5cm by 5cm in size are prepared and used to model a joint rock mass around tunnel face. Weak zones are simulated ahead of tunnel face with a material which has relatively higher conductivity than concrete blocks. Experimental results on the model test show a good agreement with analytical results.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9367-9373
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• 2014

In diagnosis of lung cancer, rapid distinction between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) tumors is very important. Serum markers, including lactate dehydrogenase (LDH), C-reactive protein (CRP), carcino-embryonic antigen (CEA), neurone specific enolase (NSE) and Cyfra21-1, are reported to reflect lung cancer characteristics. In this study classification of lung tumors was made based on biomarkers (measured in 120 NSCLC and 60 SCLC patients) by setting up optimal biomarker joint models with a powerful computerized tool - gene expression programming (GEP). GEP is a learning algorithm that combines the advantages of genetic programming (GP) and genetic algorithms (GA). It specifically focuses on relationships between variables in sets of data and then builds models to explain these relationships, and has been successfully used in formula finding and function mining. As a basis for defining a GEP environment for SCLC and NSCLC prediction, three explicit predictive models were constructed. CEA and NSE are requentlyused lung cancer markers in clinical trials, CRP, LDH and Cyfra21-1 have significant meaning in lung cancer, basis on CEA and NSE we set up three GEP models-GEP 1(CEA, NSE, Cyfra21-1), GEP2 (CEA, NSE, LDH), GEP3 (CEA, NSE, CRP). The best classification result of GEP gained when CEA, NSE and Cyfra21-1 were combined: 128 of 135 subjects in the training set and 40 of 45 subjects in the test set were classified correctly, the accuracy rate is 94.8% in training set; on collection of samples for testing, the accuracy rate is 88.9%. With GEP2, the accuracy was significantly decreased by 1.5% and 6.6% in training set and test set, in GEP3 was 0.82% and 4.45% respectively. Serum Cyfra21-1 is a useful and sensitive serum biomarker in discriminating between NSCLC and SCLC. GEP modeling is a promising and excellent tool in diagnosis of lung cancer.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.5
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• pp.375-380
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• 2017

This paper reports the results of an acceleration test to predict the contact-induced failure that could occur at the cylinder-to-hole joint for the fuel rod of a sodium-cooled fast reactor (SFR). To incorporate the fuel life of the SFR currently under development at KAERI (around 35,000 h), the acceleration test method of reliability engineering was adopted in this work. A finite element method was used to evaluate the flow-induced vibration frequency and amplitude for the test parameter values. Five specimens were tested. The failure criterion during the life of the SFR fuel was applied. The S-N curve of the HT-9, the material of concern, was used to obtain the acceleration factor. As a result, a test time of 16.5 h was obtained for each specimen. It was concluded that the $B_{0.004}$ life would be guaranteed for the SFR fuel rods with 99％ confidence if no failure was observed at any of the contact surfaces of the five specimens.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.635-642
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• 2014

In this paper, an efficient technique is developed to predict failure probability of three failure modes(case rupture, fracture and bolt breakage) related to solid rocket motor case due to the inner pressure during the mission flight. The overall procedure consists of the steps: 1) design parameters affecting the case failure are identified and their uncertainties are modelled by probability distribution, 2) combustion analysis in the interior of the case is carried out to obtain maximum expected operating pressure(MEOP), 3) stress and other structural performances are evaluated by finite element analysis(FEA), and 4) failure probabilities are calculated for the above mentioned failure modes. Axi-symmetric assumption for FEA is employed for simplification while contact between bolted joint is accounted for. Efficient procedure is developed to evaluate failure probability which consists of finding first an Most Probable Failure Point(MPP) using First-Order Reliability Method(FORM), next making a response surface model around the MPP using Latin Hypercube Sampling(LHS), and finally calculating failure probability by employing Importance Sampling.

• Journal of Korean Society of Forest Science
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• v.99 no.4
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• pp.479-486
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• 2010

We analyzed the relationships between the daily yield and quality of pine-mushroom to predict the annual production pattern and unit price of the mushroom with the records of pine-mushroom trade at Yeongdeok forestry cooperative's market for nine years (2000~2008). Although there were some exceptions due to extreme drought or extraordinary temperature, the production ratio of high quality (first and second grade) was more than 50% in early stage and decreased, while that of low quality (pileus opened and defected ones) showed increasing pattern after the production reached in peak. The ratio of high quality and that of low quality were reversed 1~9 days before the mushroom production reached the acme of daily yield, which allowed us to predict that the mushroom production would be decreased when the ratio of low quality overcomes that of high quality. The ratio of high quality preceded about 3~4 days prior to that of daily yield, and the mushroom yield showed significant correlations with the ratio of high quality mushroom prior to 3~4 days of the day with the coefficient larger than 0.5 (r=0.51 for 3 days and r=0.54 for 4 days). Thus, we concluded that the analysis of grade distribution of pine-mushroom at the market may provide a significant clue to predict production pattern of the mushroom. In addition, the price of high quality pine-mushroom showed clear negative correlations with the yield. Thus, the analysis may take a good role for the trading of pine-mushroom with providing information for predicting the price of pine-mushroom.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.242-250
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• 2019

In this paper, we propose a method to predict the failure of industrial robot using Seq2Seq (Sequence to Sequence) model, which is a model for transforming time series data among Artificial Neural Network models. The proposed method uses the data of the joint current and angular value, which can be measured by the robot itself, without additional sensor for fault diagnosis. After preprocessing the measured data for the model to learn, the Seq2Seq model was trained to convert the current to angle. Abnormal degree for fault diagnosis uses RMSE (Root Mean Squared Error) during unit time between predicted angle and actual angle. The performance evaluation of the proposed method was performed using the test data measured under different conditions of normal and defective condition of the robot. When the Abnormal degree exceed the threshold, it was classified as a fault, and the accuracy of the fault diagnosis was 96.67% from the experiment. The proposed method has the merit that it can perform fault prediction without additional sensor, and it has been confirmed from the experiment that high diagnostic performance and efficiency are available without requiring deep expert knowledge of the robot.

• Journal of Korean Orthopaedic Sports Medicine
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• v.10 no.1
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• pp.35-40
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• 2011

Purpose: This study was performed to evaluate the diagnostic usefulness of ankle stress radiograph for evaluation of chronic lateral ankle instability. Materials and Methods: Among patients undergoing the modified-Brostrom procedure, 42 cases with complete rupture of the anterior talofibular ligament were enrolled in this study. Sixty Korean adults (120 cases) were recruited as the control group. Radiologic measurement of talar tilt and anterior talar translation was performed through stress radiographs using Telos device. We obtained the normal range of Korean adults, and used as a standard value for judgment of mechanical instability. We analyzed the sensitivity, specificity, positive and negative prediction value of ankle stress radiograph. Results: On ankle stress radiograph, normal range of talar tilt angle and anterior talar translation was below $8.3^{\circ}$, below 7.6mm. Talar tilt angle on varus stress radiograph showed 57% of sensitivity, 97% of specificity, 89% of positive and 86% of negative prediction value. Anterior talar translation on anterior drawer stress radiograph showed 69% of sensitivity, 97% of specificity, 91% of positive and 90% of negative prediction value. Conclusion: Ankle stress radiograph had a good specificity, positive and negative prediction value for the evaluation of mechanical instability. However it underestimated the mechanical instability of ankle joint. It must be remembered that normal stress radiograph does not exclude ankle instability.

• Journal of Welding and Joining
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• v.30 no.6
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• pp.126-132
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• 2012

The GMA welding process involves large number of interdependent variables which may affect product quality, productivity and cost effectiveness. The relationships between process parameters for a fillet joint and bead geometry are complex because a number of process parameters are involved. To make the automated GMA welding, a method that predicts bead geometry and accomplishes the desired mechanical properties of the weldment should be developed. The developed method should also cover a wide range of material thicknesses and be applicable for all welding position. For the automatic welding system, the data must be available in the form of mathematical equations. In this study a new intelligent model with genetic algorithm has been proposed to investigate interrelationships between welding parameters and bead geometry for the automated GMA welding process. Through the developed model, the correlation between process parameters and bead geometry obtained from the actual experimental results, predicts that data did not show much of a difference, which means that it is quite suitable for the developed genetic algorithm. Progress to be able to control the process parameters in order to obtain the desired bead shape, as well as the systematic study of the genetic algorithm was developed on the basis of the data obtained through the experiments in this study can be applied. In addition, the developed genetic algorithm has the ability to predict the bead shape of the experimental results with satisfactory accuracy.