• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.80-98
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• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• Physical Therapy Korea
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• v.23 no.2
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• pp.11-19
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• 2016

Background: In the stroke patients with the characteristics of hemiplegic gait, turning direction of the affected and unaffected side influences turning time. Therefore, it is important to investigate the walking response to turning directions in stroke patients. Objects: This study aimed to measure the walking time while turning direction in hemiplegic patients depending on balance ability measured by Berg Balance Scale. Methods: A group of forty-five subjects with stroke (Berg Balance Scale score${\geq}46$ were twenty-eight, Berg Balance Scale score${\leq}45$ were seventeen) were enrolled in this study. Subjects were asked to perform the Timed Up and Go test. Testing indications included two directions for turning in each subject. These indications were for turning toward the affected and unaffected side in stroke patients. The duration of total analysis duration, sit to stand phase, stand to sit phase, mid-turning phase, and end turning phase were recorded. The obtained data were analyzed by using paired t-test and Wilcoxon signed rank test in the group that are below and above 45 points of Berg Balance Scale score. The significance level was set at ${\alpha}=.05$. Results: There were significant increase time in the analysis duration and end turning phase duration while subjects were turned the unaffected side in stroke patients that presented a Berg Balance Scale score${\leq}45$ (p<.05). However, the comparison between the affected side and the unaffected side in the stroke patients with Berg Balance Scale score${\geq}46$, revealed no significant differences of the measured parameters. Conclusion: This finding should be suggested in the specific definition of turning direction for evaluation with Timed Up and Go test in the Berg Balance Scale score${\leq}45$, and other intervention for hemiplegic patients need to be suggested the direction of turning during walking training program.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.218-226
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• 2020

An experimental study was conducted on baseline model updating and damage estimation techniques for the health monitoring of offshore wind turbine tripod substructures. First, a procedure for substructure health monitoring was proposed. An initial baseline model for a scaled model of a tripod substructure was established. A baseline model was updated based on the natural frequencies and the mode shapes measured in the healthy state. A training pattern was then generated using the updated baseline model, and the damage was estimated by inputting the modal parameters measured in the damaged state into the trained neural network. The baseline model could be updated reasonably using the effective fixity model. The damage tests were performed, and the damage locations could be estimated reasonably. In addition, the estimated damage severity also increased as the actual damage severity increased. On the other hand, when the damage severity was relatively small, the corresponding damage location was detected, but it was more difficult to identify than the other cases. Further studies on small damage estimation and stiffness reduction quantification will be needed before the presented method can be used effectively for the health monitoring of tripod substructures.

• Parasites, Hosts and Diseases
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• v.55 no.4
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• pp.367-374
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• 2017

Despite the broad distribution of leishmaniasis among Iranians and animals across the country, little is known about the genetic characteristics of the causative agents. Applying both HSP70 PCR-RFLP and sequence analyses, this study aimed to evaluate the genetic diversity and phylogenetic relationships among Leishmania spp. isolated from Iranian endemic foci and available reference strains. A total of 36 Leishmania isolates from almost all districts across the country were genetically analyzed for the HSP70 gene using both PCR-RFLP and sequence analysis. The original HSP70 gene sequences were aligned along with homologous Leishmania sequences retrieved from NCBI, and subjected to the phylogenetic analysis. Basic parameters of genetic diversity were also estimated. The HSP70 PCR-RFLP presented 3 different electrophoretic patterns, with no further intraspecific variation, corresponding to 3 Leishmania species available in the country, L. tropica, L. major, and L. infantum. Phylogenetic analyses presented 5 major clades, corresponding to 5 species complexes. Iranian lineages, including L. major, L. tropica, and L. infantum, were distributed among 3 complexes L. major, L. tropica, and L. donovani. However, within the L. major and L. donovani species complexes, the HSP70 phylogeny was not able to distinguish clearly between the L. major and L. turanica isolates, and between the L. infantum, L. donovani, and L. chagasi isolates, respectively. Our results indicated that both HSP70 PCR-RFLP and sequence analyses are medically applicable tools for identification of Leishmania species in Iranian patients. However, the reduced genetic diversity of the target gene makes it inevitable that its phylogeny only resolves the major groups, namely, the species complexes.

• Journal of the Korea Concrete Institute
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• v.27 no.4
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• pp.331-341
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• 2015

The main purpose of this study is reducing the cost and effort for characterization of tensile strength of fiber reinforced concrete, in order to use in structural design. For this purpose, in this study, test for fiber reinforced concrete was carried out. Because fiber reinforced concrete is consisted of diverse material, it is hard to define the correlation between mix proportions and strength. Therefore, compressive strength test and tensile strength test were carried out for the range of smaller than 100 MPa of compressive strength and 0.25~1% of steel fiber volume fraction. as a results of test, two types of tensile strength were highly affected by compressive strength of concrete. However, increase rate of tensile strength was decreased with increase of compressive strength. Increase rate of tensile strength was decreased with increase of fiber volume fraction. Database was constructed using previous research data. Because estimation equations for tensile strength of fiber reinforced concrete should be multiple variable function, linear regression is hard to apply. Therefore, in this study, we decided to use the ANN(Artificial Neural Network). ANN was constructed using multiple layer perceptron architecture. Sigmoid function was used as transfer function and back propagation training method was used. As a results of prediction using artificial neural network, predicted values of test data and previous research which was randomly selected were well agreed with each other. And the main effective parameters are water-cement ratio and fiber volume fraction.

• Analytical Science and Technology
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• v.24 no.6
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• pp.544-555
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• 2011

The acute toxicity in the rainbow trout (Oncorhynchus mykiss) was analyzed and predicted using quantitative structure-activity relationships (QSAR). The aquatic toxicity, 96h $LC_{50}$ (median lethal concentration) of 275 organic pesticides, was obtained from EU-funded project DEMETRA. Prediction models were derived from 558 2D molecular descriptors, calculated in PreADMET. The linear (multiple linear regression) and nonlinear (support vector machine and artificial neural network) learning methods were optimized by taking into account the statistical parameters between the experimental and predicted p$LC_{50}$. After preprocessing, population based forward selection were used to select the best subsets of descriptors in the learning methods including 5-fold cross-validation procedure. The support vector machine model was used as the best model ($R^2_{CV}$=0.677, RMSECV=0.887, MSECV=0.674) and also correctly classified 87% for the training set according to EU regulation criteria. The MLR model could describe the structural characteristics of toxic chemicals and interaction with lipid membrane of fish. All the developed models were validated by 5 fold cross-validation and Y-scrambling test.

• Fire Science and Engineering
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• v.28 no.4
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• pp.104-111
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• 2014

The purpose of this study is to investigate the CPR within ambulance. The Subjects were 890 emergency medical technicians in fire department in Gyeonggido. After continuing education program, the emergency medical technicians completed the questionnaires from January to February, 2012. Questionnaire consisted of demographic characteristics, method of chest compression (one handed or two handed), chest compression - ventilation ratio, and hands only CPR. Data were analyzed by frequency analysis and Chi-square test, t-test. One-way analysis of variance (ANOVA) was followed by Scheffe post-hoc test to analyze changes in all parameters between all groups. One handed chest compression accounted for 14.0% and two handed chest compression accounted for 86.0%. Hands only CPR accounted for 71.7% and standard CPR (30:2) accounted for 28.3%. In order to perform the high quality CPR, as least three persons must be dispatched in the ambulance. The flexible management of manpower may improve the survival from the cardiac arrest. A systemic approach for educating and training EMT's in CPR is needed.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.11
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• pp.4999-5003
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• 2016

The testicular cancer (TCa) incidence is increasing in many countries, with age-standardized incidence rates up to 7.8/100,000 men in the Western world, although reductions in mortality and increasingly high cure rates are being witnessed at the same time. In Africa, where rates are lower, presentation is often late and morbidity and mortality high. Given this scenario, awareness of testicular cancer and practice of testicular self-examination among future first response doctors is very important. This study was conducted to determine knowledge and attitude to testicular cancer, and practice of testicular self-examination (TSE) among final (6th) year medical students. In addition, the effect of an intervention in the form of a single PowerPoint(R) lecture, lasting 40 minutes with image content on testicular cancer and testicular self examination was assessed. Pre and post intervention administration of a self-administered structured pre tested questionnaire was performed on 151 medical students, 101 of whom returned answers (response rate of 66.8%). In the TC domain, there was a high level of awareness of testicular cancer, but poor knowledge of the age group most affected, with significant improvement post intervention (p<0.001). Notable also was the poor awareness of the potential curability of TC, this also being improved following the intervention (p<0.001). A poor level of awareness and practice of testicular self-examination pre-intervention was found considering the nature of the study group..Respondents had surprisingly weak/poor responses to the question "How important to men's health is regular testicular self-examination?" Answers to the questions "Do you think it is worthwhile to examine your testis regularly?" and "Would you be interested in more information on testicular cancer and testicular self-examination?" were also suboptimal, but improved post intervention p<0.001, p<0.001 and p=0.037. Age, gender and marital status were without specific influence. In conclusion, this study showed poor levels of knowledge regarding epidemiology of TCa and its potential curability when detected early. There was also a poor awareness of, practice of, and poor attitudes to TSE. The significant improvement in these parameters post intervention indicates value in educational intervention. We recommend inclusion of TCa coverage and TSE teaching in the secondary school curriculum (targeting adolescents). Greater emphasis should also be given to testicular cancer in the curricula of medical schools and other training institutions for health care personnel.

• Geophysics and Geophysical Exploration
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• v.23 no.3
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• pp.168-177
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• 2020

Seabed multiple reflections (seabed multiples) are the main cause of misinterpretations of primary reflections in both shot gathers and stack sections. Accordingly, seabed multiples need to be suppressed throughout data processing. Conventional model-driven methods, such as prediction-error deconvolution, Radon filtering, and data-driven methods, such as the surface-related multiple elimination technique, have been used to attenuate multiple reflections. However, the vast majority of processing workflows require time-consuming steps when testing and selecting the processing parameters in addition to computational power and skilled data-processing techniques. To attenuate seabed multiples in seismic reflection data, input gathers with seabed multiples and label gathers without seabed multiples were generated via numerical modeling using the Marmousi2 velocity structure. The training data consisted of normal-moveout-corrected common midpoint gathers fed into a U-Net neural network. The well-trained model was found to effectively attenuate the seabed multiples according to the image similarity between the prediction result and the target data, and demonstrated good applicability to field data.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.7
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• pp.3015-3021
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• 2015

Background: Colorectal cancer (CRC) is a major cause of mortality in developed countries, and it is the third most frequent malignancy in Turkey. There are many biological, genetic, molecular, and tissue-derived prognostic factors for CRCs. In this study, we evaluated prognostic factors in patients who were metastatic at diagnosis or progressed to metastatic disease during follow-up. Patients and Methods: This study included 116 patients with malignancies either in the colon or rectum. Of these, 65 had metastatic disease at diagnosis, and 51 progressed to metastatic disease during the course of the disease. The parameters evaluated were age, gender, comorbidity, performance status and stage of the disease at the beginning, localization, history of surgery, chemotherapy regimen, response to first-line treatment, K-RAS status, site and number of metastases, expression of tumor predictors (CEA, CA19-9), and survival times. A multivariate analysis conducted with factors that considered statistically significant in the univariate analysis. Findings: Median age was 56 (32-82) years and the male/female ratio was 80/36. Eleven patients were at stage II, 40 at stage III, and 65 at stage IV at diagnosis. Twenty three patients had tumor in the right colon, 48 in the left colon, and 45 in the rectum. Ninety seven patients were operated, and 27 had surgical metastasectomy. Ninety three patients received targeted therapy. At the end of follow-up, 61 patients had died, and 55 survived. Metastatic period survival times were longer in the adjuvant group, but the difference did not reach the level of statistical significance (adjuvant group: median 29 months, metastatic group: median 22 months; p=0.285). In the adjuvant group before the metastatic first-line therapy, CEA and CA 19-9 levels were significiantly lower compared to the metastatic group (p<0.005). We also found that patients with elevated tumor predictor (CEA, CA 19-9) levels before the first-line therapy had significiantly poorer prognosis and shorter survival time. Survival was significiantly better with the patients who were younger than 65 years of age, had better initial performance status, a history of primary surgery and metastatectomy, and single site of metastasis. Those who benefitted from the first-line therapy were K-RAS wild type and whose tumor markers (CEA, CA 19-9) were not elevated before the first line therapy. Conclusions: Among the patients with metastatic CRC, those who benefited from first-line therapy, had history of metastasectomy, were K-RAS wild type and had low CA 19-9 levels before the first-line therapy, showed better prognosis independent of other factors.