• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1493-1498
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• 2016

Background: Breast cancer is the most common cancer in women worldwide with a rising incidence rate in most countries. Considering the increase in life expectancy and change in lifestyle of Iranian women, this study investigated the age-adjusted trend of breast cancer incidence during 2000-2009 and predicted its incidence to 2020. Materials and Methods: The 1997 and 2006 census results were used for the projection of female population by age through the cohort-component method over the studied years. Data from the Iranian cancer registration system were used to calculate the annual incidence rate of breast cancer. The age-adjusted incidence rate was then calculated using the WHO standard population distribution. The five-year-age-specific incidence rates were also obtained for each year and future incidence was determined using the trend analysis method. Annual percentage change (APC) was calculated through the joinpoint regression method. Results: The bias adjusted incidence rate of breast cancer increased from 16.7 per 100,000 women in 2000 to 33.6 per 100,000 women in 2009. The incidence of breast cancer had a growing trend in almost all age groups above 30 years over the studied years. In this period, the age groups of 45-65 years had the highest incidence. Investigation into the joinpoint curve showed that the curve had a steep slope with an APC of 23.4% before the first joinpoint, but became milder after this. From 2005 to 2009, the APC was calculated as 2.7%, through which the incidence of breast cancer in 2020 was predicted as 63.0 per 100,000 women. Conclusions: The age-adjusted incidence rate of breast cancer continues to increas in Iranian women. It is predicted that this trend will continue until 2020. Therefore, it seems necessary to prioritize the prevention, control and care for breast cancer in Iran.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6427-6431
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• 2013

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers in the world and deeply threatens people's health, especially in China. Techniques of early diagnosis, prevention and prediction are still being discovered, among which the approaches based on single nucleotide polymorphisms in microRNA genes (miRNA SNPs) are newly proposed and show prospective potential. In particular, the association between SNPs in miRNA196a-2 (rs11614913) and miRNA146a (rs2910164) and HCC has been investigated. However, the conclusions made were conflicting, possibly due to insufficient sample size or population stratification. Further confirmations in well-designed large samples are still required. In this study, we verified the association between these two SNPs and the susceptibility to HCC by MassARRAY assay in a 2,000 large Chinese case-control sample. Significant association between rs11614913 and HCC was confirmed. Subjects with the genotype of CT+TT or T allele in rs11614913 were more resistant to HCC (CT+TT: OR (95% CI)=0.73 (0.57-0.92), P=0.01; T allele: OR (95% CI)=0.85 (0.75-0.97), P=0.02) and HBV-related HCC (CT+TT: OR (95% CI)=0.69 (0.53-0.90), P=0.01; T allele: OR (95% CI)=0.82 (0.71-0.95), P=0.01). The affected carriers of CT or TT also tended to have lower levels of serum AFP (P=0.01). This study demonstrated a role of rs11614913 in the etiology of HCC. Further research should focus on the clinical use of this miRNA SNP, so as to facilitate conquering HCC.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.303-303
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• 2017

Japanese agriculture has faced to several threats: aging and decrease of farmer population, global competition, and the risk of climate change as well as harsh and variable weather. On the other hands, the number of large scale farms is increasing, because farm lands have been being aggregated to fewer numbers of farms. Cost cutting, development of efficient ways to manage complicatedly scattered farm lands, maintaining yield and quality under variable weather conditions, are required to adapt to changing environments. Information and communications technology (ICT) would contribute to solve such problems and to create innovative technologies. Thus we have been developing an early warning and decision support system to reduce weather and climate risks for rice, wheat and soybean production in Japan. The concept and prototype of the system will be shown. The system consists of a weather data system (Agro-Meteorological Grid Square Data System, AMGSDS), decision support contents where information is automatically created by crop models and delivers information to users via internet. AMGSDS combines JMA's Automated Meteorological Data Acquisition System (AMeDAS) data, numerical weather forecast data and normal values, for all of Japan with about 1km Grid Square throughout years. Our climate-smart system provides information on the prediction of crop phenology, created with weather forecast data and crop phenology models, as an important function. The system also makes recommendations for crop management, such as nitrogen-topdressing, suitable harvest time, water control, pesticide spray. We are also developing methods to perform risk analysis on weather-related damage to crop production. For example, we have developed an algorism to determine the best transplanting date in rice under a given environment, using the results of multi-year simulation, in order to answer the question "when is the best transplanting date to minimize yield loss, to avoid low temperature damage and to avoid high temperature damage?".

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.203-203
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• 2017

The Earth's climate is rapidly changing because of increasing carbon dioxide content in atmosphere so, climate prediction models anticipate that earth surface temperature will rise by 3 to $5^{\circ}C$ in next 50 to 100 years. Therefore, frequency of un-expected weather events such as drought, salinity, low or high temperature and flooding etc. will be increasing worldwide. Furthermore, increased atmosphere temperature can influence pests and pathogens spread as well. Therefore, to protect enormous grain loss from unexpected weather conditions, studies related with combine stress conditions like abiotic plus biotic stress condition are really required. Thus, our research focused on physiological responses under combined abiotic and biotic stress condition in rice plant. To induce uniform stress condition, we used NaCl (100 mM) and salicylic acid (0.5 and 1.0 mM SA) as each stress a stimulator. Each artificial abiotic and biotic stress inducer was applied to hydroponically grown rice seedlings alone or together for four day. The data were collected in a time-dependent manner [1, 2, 3 and 4 day(s) after treatment (DAT)] and were matched with our anticipation that shoot length and shoot fresh weight was decreased in solo and combined abiotic and biotic stress condition. The lipid peroxidation content was significantly increased ($1.5{\pm}0.2$ to $2.7{\pm}0.1mg$ mg of $MDA\;g^{-1}FW$) in the first two days in both stress exposed plants, and showed the opposite trend ($0.5{\pm}0.01$ to $0.1{\pm}0.001mg$ of $MDA\;g^{-1}FW$) in last two days under multi stress condition. Superoxide dismutase (SOD) activity did not showed difference in only biotic stress condition (alone 0.5 and 1.0 mM SA) as compared to control however, it was significantly increased in multi stress condition or solo abiotic stress condition whereas, catalase (CAT), and ascorbate peroxidase (APX) activities were significantly decreased in solo biotic and combined abiotic and biotic condition. In particular, both enzymes activities were more decreased in multi stress condition as compared to solo biotic stress condition. The results for relative mRNA expression level of CAT and APX enzymes were in agreement with results of spectrophotometric values. Correlation value between each stress condition and phenotypic data showed that biotic stress condition showed high correlation with activity of CAT and APX whilst, abiotic stress condition revealed significant correlation with SOD activity.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.63-72
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• 2013

Business Process Intelligence (BPI) is one of the emerging technologies in the knowledge discovery and analysis area. BPI deals with a series of techniques from discovering knowledge to analyzing the discovered knowledge in BPM-supported organizations. By means of the BPI technology, we are able to provide the full functionality of control, monitoring, prediction, and optimization of process-supported organizational knowledge. Particularly, we focus on the focal organizational knowledge, which is so-called the BPM activity-performer affiliation networking knowledge that represents the affiliated relationships between performers and activities in enacting a specific business process model. That is, in this paper we devise a statistical analysis method to be applied to the BPM activity-performer affiliation networking knowledge, and dubbed it the activity-performer correspondence analysis method. The devised method consists of a series of pipelined phases from the generation of a bipartite matrix to the visualization of the analysis result, and through the method we are eventually able to analyze the degree of correspondences between a group of performers and a group of activities involved in a business process model or a package of business process models. Conclusively, we strongly expect the effectiveness and efficiency of the human resources allotments, and the improvement of the correlational degree between business activities and performers, in planning and designing business process models and packages for the BPM-supported organization, through the activity-performer correspondence analysis method.

• Science of Emotion and Sensibility
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• v.18 no.3
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• pp.35-48
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• 2015

It is frequently found in daily life that people who experience good luck as lottery winners try to improve their background (e.g., home, car) but it has not been empirically validated why they do that. Present research attempts to explore the prediction that people who experience good luck expand the scope of attention to background and those who undergo bad luck shrink the scope of attention to adjacent objects. Findings from Experiment 1a indicate that participants who experienced good luck (won the rock-paper-scissors game) paid more attention to background and performed worse in the "find the hidden picture" (below FHP) task while those who underwent bad luck (lost the rock-paper-scissors game) paid more attention to objects, leading to better performance in the FHP task. It is also found in Experiment 1a that, if people washed their hands after experiencing good or bad luck, the opposite result occurred. Experiment 1b confirmed that the rock-paper-scissor game manipulated good and bad luck successfully and did not influence self-control. Experiment 2 shows that people who strongly believe in good luck performed poorly in FHP task while those who do not believe in good luck performed well in FHP task. Overall, three experiments support the proposed research hypotheses. Implications of the study findings for cognitive psychology and related fields including consumer and sports psychology are discussed.

• Korean Journal of Clinical Laboratory Science
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• v.52 no.3
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• pp.181-187
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• 2020

Fecal calprotectin (FC) is a marker used for the differential diagnosis of inflammatory bowel disease (IBD). FC is also used to determine the effects of treatment and recurrence prediction because of its non-decomposition by bacteria, relative week stability at room temperature, and its uniform distribution within feces. Healthy male and female adults between the age of 30 and 80 living in Jeju were selected for this study. The FC concentration in the healthy control group (N=45) was distributed widely as 0~545.9 ㎍/g and showed a significant difference with age in healthy adults. The FC concentration in adults over 70 years old (80.6 years on average) was 160.3 ㎍/g. The result is approximately 10 times higher than in adults below 50 years (44 years on average), with FC concentrations at 15.88 ㎍/g. Moreover, adults over 50 years, with an average age of 59.6, had FC concentrations of 35.46 ㎍/g, which were two times higher than the below 50-year-old group, confirming the significant correlation between age and FC concentration. As the FC test is a non-invasive and cost-effective objective marker in IBD tests, a suitable cut-off value is required for different ages. This study provides the baseline data for differential diagnoses.

• Journal of the Korean Institute of Gas
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• v.19 no.1
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• pp.28-37
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• 2015

This study presents the development of a well placement optimization model, combining an artificial neural network, which enables high-speed calculation, with a simulated annealing algorithm. The conventional FDM simulator takes excessive time when used to perform a field scale reservoir simulation. In order to solve this problem, an artificial neural network was applied to the model to allow the simulation to be executed within a short time. Also by using the given result, the optimization method, SA algorithm, was implemented to automatically select the optimal location without taking any subjective experiences into consideration. By comparing the result of the developed model with the eclipse simulator, it was found that the prediction performance of the developed model has become favorable, and the speed of calculation performance has also been improved. Especially, the optimum value was estimated by performing a sensitivity analysis for the cooling rate and the initial temperature, which is the control parameter of SA algorithm. From this result, it was verified that the calculation performance has been improved, as well. Lastly, an optimization for the well placement was performed using the model, and it concluded the optimized place for the well by selecting regions with great productivity.

• Journal of The Korean Association For Science Education
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• v.32 no.2
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• pp.236-264
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• 2012

The purpose of this study is to provide teachers with sub-components of inquiry skills and help them to give direct instructions on the skills to their students. Inquiry skills and strategies are considered by-products of science and inquiry instruction by most of the science teachers. On the other hand, much research shows that many students are not familiar with the way that they can use inquiry skills therefore direct instruction on the inquiry skills is needed. The lack of guidance on the sub-components for the inquiry skills, however, results in science teachers' ignorance of the inquiry skills. As shown in the previous studies which suggest that without teachers' guidance, students cannot acquire the intended skills, and it is necessary to inform science teachers of the necessity for direct instruction on the inquiry skills and strategy as well as give them the sub-components of the inquiry skills. On the basis of the results from the previous research on the inquiry skills, this study presents the sub-components of basic inquiry skills (observation, classification, measure, prediction, and reasoning) and integrated inquiry skills (problem recognition, hypothesis formulation, control of variables, data transformation, data interpretation, drawing conclusion, and generalization).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5B
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• pp.405-414
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• 2011

The adaptive network-based fuzzy inference system (ANFIS) which had a success for time series prediction and system control was applied for modeling the hourly runoff in the Gapcheon watershed. The ANFIS used the antecedent rainfall and runoff as the input. The ANFIS was trained by varying the various simulation factors such as mean areal rainfall estimation, the number of input variables, the type of membership function and the number of membership function. The root mean square error (RMSE), mean peak runoff error (PE), and mean peak time error (TE) were used for validating the ANFIS simulation. The ANFIS predicted runoff was in good agreement with the measured runoff and the applicability of ANFIS for modelling the hourly runoff appeared to be good. The forecasting ability of ANFIS up to the maximum 8 lead hour was investigated by applying the different input structure to ANFIS model. The accuracy of ANFIS for predicting the hourly runoff was reduced as the forecasting lead hours increased. The long-term predictability of ANFIS for forecasting the hourly runoff at longer lead hours appeared to be limited. The ANFIS might be useful for modeling the hourly runoff and has an advantage over the physically based models because the model construction of ANFIS based on only input and output data is relatively simple.