• Journal of the Korea Institute of Building Construction
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• v.19 no.6
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• pp.503-510
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• 2019

Recently, construction technology of RC structures must be examined for creep in concrete. The factors affecting the creep prediction of concrete and the results of creep in domestic construction field were reviewed. The longer the creep test period and the higher the compressive strength, the higher the creep prediction accuracy. The higher the curing temperature, the higher the initial strength development of the concrete, but the difference in the creep coefficients increased over time. Based on the results of creep evaluation in the domestic construction field and lab. tests, a modified predictive model that complements the ACI-209 model was proposed. In the creep prediction of real members using general to high strength concrete, the test period and temperature should be considered precisely.

• Parasites, Hosts and Diseases
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• v.51 no.6
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• pp.763-766
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• 2013

A synthetic peptide was prepared based on the antigenic region of Paragonimus westermani pre-procathepsin L, and its applicability for immunodiagnosis for human paragonimiasis (due to Paragonimus heterotremus) was tested using an ELISA to detect IgG4 antibodies in the sera of patients. Sera from other helminthiases, tuberculosis, and healthy volunteers were used as the references. This peptide-based assay system gave sensitivity, specificity, accuracy, and positive and negative predictive values of 100%, 94.6%, 96.2%, 100%, and 88.9%, respectively. Cross reactivity was frequently seen against the sera of fascioliasis (75%) and hookworm infections (50%). Since differential diagnosis between paragonimiasis and fascioliasis can be easily done by clinical presentation and fascioliasis serology, this cross reaction is not a serious problem. Sera from patients with other parasitoses (0-25%) rarely responded to this synthetic antigen. This synthetic peptide antigen seems to be useful for development of a standardized diagnostic system for paragonimiasis.

• KIISE Transactions on Computing Practices
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• v.22 no.3
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• pp.127-132
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• 2016

Several methods have been proposed to apply artificial neural networks to text compression in the past. However, the networks and targets are both limited to the small size due to hardware capability in the past. Modern GPUs have much better calculation capability than CPUs in an order of magnitude now, even though CPUs have become faster. It becomes possible now to train greater and complex neural networks in a shorter time. This paper proposed a method to transform the distribution of original data with a probabilistic neural predictor. Experiments were performed on a feedforward neural network and a recurrent neural network with gated-recurrent units. The recurrent neural network model outperformed feedforward network in compression rate and prediction accuracy.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.2
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• pp.1-13
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• 2017

In This Paper, we find the Target Candidate Region and the Location of the Candidate Region by Performing the Morphological Difference Calculation and Pixel Labeling for Robust Small Target Detection in Infrared Image with low SNR. Conventional Target Detection Methods based on Morphology Algorithms are low in Detection Accuracy due to their Vulnerability to Clutter in Infrared Images. To Address the Problem, Target Signal Enhancement and Background Clutter Suppression are Achieved Simultaneously by Combining Moravec Algorithm and LCM (Local Contrast Measure) Algorithm to Classify the Target and Noise in the Candidate Region. In Addition, the Proposed Algorithm can Efficiently Detect Multiple Targets by Solving the Problem of Limited Detection of a Single Target in the Target Detection method using the Morphology Operation and the Gaussian Distance Function Which were Developed for Real time Target Detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.321-340
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• 2016

The Compressive Video Sensing (CVS) is a useful technology for wireless systems requiring simple encoders but handling more complex decoders, and its rate-distortion performance is highly affected by the quantization of measurements and reconstruction of video frame, which motivates us to presents the Space-Time Quantization (ST-Q) and Motion-Aligned Reconstruction (MA-R) in this paper to both improve the performance of CVS system. The ST-Q removes the space-time redundancy in the measurement vector to reduce the amount of bits required to encode the video frame, and it also guarantees a low quantization error due to the fact that the high frequency of small values close to zero in the predictive residuals limits the intensity of quantizing noise. The MA-R constructs the Multi-Hypothesis (MH) matrix by selecting the temporal neighbors along the motion trajectory of current to-be-reconstructed block to improve the accuracy of prediction, and besides it reduces the computational complexity of motion estimation by the extraction of static area and 3-D Recursive Search (3DRS). Extensive experiments validate that the significant improvements is achieved by ST-Q in the rate-distortion as compared with the existing quantization methods, and the MA-R improves both the objective and the subjective quality of the reconstructed video frame. Combined with ST-Q and MA-R, the CVS system obtains a significant rate-distortion performance gain when compared with the existing CS-based video codecs.

• Journal of Yeungnam Medical Science
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• v.20 no.2
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• pp.117-128
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• 2003

Thallium-201 scintigraphy is used to discriminate the malignant bone tumor from the benign by qualitatively and quantitatively, and to predict the response of preoperative chemotherapy in osteosarcoma, by comparing the changes of thallium uptake ratio after chemotherapy to the tumor necrosis ratio. Thallium-201 scintigraphy scan should be done prior to surgical biopsy. PICKER Prism 2000 gamma camera with high resolution parallel hole collimator is usually used for scanning. The patient is injected with 2-3mCi of Tl-201 and the early phase is checked in 30 minutes and delayed phase in 3 hours. The scan images are visually evaluated by a blinded nuclear medicine physician. We could evaluate true positive, true negative, false positive and false negative by the comparison of results with those of biopsy, and calculate positive and negative predictive value(%), sensitivity(%), specificity(%) and diagnostic accuracy(%). For the quantitative analysis of thallium uptake, we drew the region of interest on the tumor side and contralateral normal side as mirror image, and calculated the uptake ratio with dividing the amount of gamma count in tumor side by normal side. We could calculate the percent changes of thallium uptake ratio in early and delayed phase, and compare them to the ratio of tumor necrosis. Thallium-201 scintigraphy proved as useful imaging study to discriminate malignant bone tumor from benign, but had exception in giant cell tumor and low grade malignant bone tumors. We can use T1-201 scan to differentiate the benign from the malignant tumor, and to evaluate the response of preoperative chemotherapy or radiotherapy, and to determine the residual tumor or local recurrence. For the better result, we need to have a more detail information about false positive cases and a more objective and quantitative reading technique.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6819-6822
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• 2014

Background: The aim of this study was to evaluate the accuracy of a new scoring system in Korean patients with hematuria at high risk of bladder cancer. Materials and Methods: A total of 319 consecutive patients presenting with painless hematuria without a history of bladder cancer were analyzed, from the period of August 2012 to February 2014. All patients underwent clinical examination, and 22 patients with incomplete data were excluded from the final validation data set. The scoring system included four clinical parameters: age (${\geq}50$ = 2 vs. <50 =1), gender (male = 2 vs. female = 1), history of smoking (smoker/ex-smoker = 4 vs. non-smoker = 2) and nature of the hematuria (gross = 6 vs. microscopic = 2). Results: The area under the receiver-operating characteristic curve (95% confidence interval) of the scoring system was 0.718 (0.655-0.777). The calibration plot demonstrated a slight underestimation of bladder cancer probability, but the model had reasonable calibration. Decision curve analysis revealed that the use of model was associated with net benefit gains over the treat-all strategy. The scoring system performed well across a wide range of threshold probabilities (15%-45%). Conclusions: The scoring system developed is a highly accurate predictive tool for patients with hematuria. Although further improvements are needed, utilization of this system may assist primary care physicians and other healthcare practitioners in determining a patient's risk of bladder cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7257-7260
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• 2013

To determine the pattern of disease in patients presenting with breast lumps and to determine the sensitivity and specificity of fine needle aspiration cytology of benign and malignant diseases as a diagnostic tool by correlating with histopathology findings. This retrospective study was carried out in the Department of Pathology, Maharaja Agrasen Medical College, Agroha, from Jan 2008 to April 2012. Fine needle aspiration cytology was performed on 370 cases and out of these 52 cases were received in the Department for histopathological examination. Fibroadenoma was the most common disease encountered, in 88 (24%), with a peak incidence in second and third decade of life. Fibrocystic disease was second, being common in the third and fourth decades of life. Peak incidences of duct ectasia, granulomatous and tubercular mastitis were seen in the third decade. Gynaecomastia showed two peak incidences in second and sixth decades of life. Out of total 370 cases undergoing fine needle aspiration, benign cases were 316 (85.4%), malignant and suspicious were 54 (14.6%) and 10 (2.70%) respectively. Out of total 22 histological confirmed malignant lesions 19 were interpreted as malignant cytologically while two as suspicious and one as benign. All thirty histologically confirmed benign cases were diagnosed as benign cytologically. The sensitivity, specificity, positive and negative predictive values were 98%, 100%, 100% and 96.4% respectively. FNA cytology is highly accurate for diagnosis of breast masses. However, the clinician should correlate FNA cytological results with physical examination and imaging findings to prevent false negative and false positive events and to obtain optimal management of their patients.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.7
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• pp.378-388
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• 2000

In this paper, we propose Fuzzy Polynomial Neural Networks(FPNN) based on Polynomial Neural Networks(PNN) and Fuzzy Neural Networks(FNN) for model identification of complex and nonlinear systems. The proposed FPNN is generated from the mutually combined structure of both FNN and PNN. The one and the other are considered as the premise part and consequence part of FPNN structure respectively. As the consequence part of FPNN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. FPNN is available effectively for multi-input variables and high-order polynomial according to the combination of FNN with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. As the premise part of FPNN, FNN uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. And we use two kinds of FNN structure according to the division method of fuzzy space of input variables. One is basic FNN structure and uses fuzzy input space divided by each separated input variable, the other is modified FNN structure and uses fuzzy input space divided by mutually combined input variables. In order to evaluate the performance of proposed models, we use the nonlinear function and traffic route choice process. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously. And also performance index related to the approximation and prediction capabilities of model is evaluated and discussed.

• KIISE Transactions on Computing Practices
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• v.23 no.11
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• pp.632-640
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• 2017

Although solar insolation is the weather factor with the greatest influence on power generation in photovoltaic systems, the Meterological Agency does not provide solar insolation data for future dates. Therefore, it is essential to research prediction methods for solar insolation to efficiently manage photovoltaic systems. In this study, we propose a Dynamic Piecewise Prediction Model that can be used to predict solar insolation values for future dates based on information from the weather forecast. To improve the predictive accuracy, we dynamically divide the entire data set based on the sun altitude and cloudiness at the time of prediction. The Dynamic Piecewise Prediction Model is developed by applying a polynomial linear regression algorithm on the divided data set. To verify the performance of our proposed model, we compared our model to previous approaches. The result of the comparison shows that the proposed model is superior to previous approaches in that it produces a lower prediction error.