Multiple Criteria Decision-Making Preprocessing Using Data Mining Tools

Real-life engineering optimization problems need Multiobjective Optimization (MOO) tools. These problems are highly nonlinear. As the process of Multiple Criteria Decision-Making (MCDM) is much expanded most MOO problems in different disciplines can be classified on the basis of it. Thus MCDM methods have gained wide popularity in different sciences and applications. Meanwhile the increasing number of involved components, variables, parameters, constraints and objectives in the process, has made the process very complicated. However the new generation of MOO tools has made the optimization process more automated, but still initializing the process and setting the initial value of simulation tools and also identifying the effective input variables and objectives in order to reach the smaller design space are still complicated. In this situation adding a preprocessing step into the MCDM procedure could make a huge difference in terms of organizing the input variables according to their effects on the optimization objectives of the system. The aim of this paper is to introduce the classification task of data mining as an effective option for identifying the most effective variables of the MCDM systems. To evaluate the effectiveness of the proposed method an example has been given for 3D wing design.Comment: International Journal of Computer Science Issues at http://ijcsi.org/articles/Multiple-Criteria-Decision-Making-Preprocessing-Using-Data-Mining-Tools.ph

Combining mammaglobin and carcinoembryonic mRNA markers for early detection of micrometastases from breast cancers - a molecular study of 59 patients

Introduction: As many as 30% of node-negative breast cancer patients relapse within five years, suggesting that current histological detection methods are inadequate for identifying metastatic disease. Detecting small number of cancer cells in the breast tissue or lymph node by reverse transcription-polymerase chain reaction (RT-PCR) assays using a combination of tissue and cancer specific markers might be very useful in the early detection or monitoring of the treatment. Mammaglobin is a member of the uteroglobin gene family and appears to be expressed only in breast tissue. Carcinoembryonic antigen has been the preferred molecular marker for detection of micro metastases in lymph nodes in almost all carcinomas. Materials and Methods: Samples were collected from randomly chosen breast cancer patients undergoing modified mastectomy or breast conserving surgery between September 2003 and July 2004. RT-PCR was applied to study the expression of MMG and CEA markers. Breast cancer micrometastases in axillary lymph nodes were also assessed. Results: The MMG marker was positive in 9/10 normal breast tissues, 3/ 3 breast fibroadenomas and 37/39 of breast carcinoma tissues, giving an overall sensitivity of 94%. The sensitivity was 80% for metastatic lymph node samples. On the other hand CEA showed 95% sensitivity for malignant breast tumors and 100% sensitivity for metastatic lymph nodes. Conclusions: RT-PCR using a combination of MMG and CEA markers is a powerful tool to complement current routine histopathology techniques for detection of breast cancer metastasis in axillary nodes

Aligning Manifolds of Double Pendulum Dynamics Under the Influence of Noise

This study presents the results of a series of simulation experiments that evaluate and compare four different manifold alignment methods under the influence of noise. The data was created by simulating the dynamics of two slightly different double pendulums in three-dimensional space. The method of semi-supervised feature-level manifold alignment using global distance resulted in the most convincing visualisations. However, the semi-supervised feature-level local alignment methods resulted in smaller alignment errors. These local alignment methods were also more robust to noise and faster than the other methods.Comment: The final version will appear in ICONIP 2018. A DOI identifier to the final version will be added to the preprint, as soon as it is availabl

Effect of aqueous extract of Althaea root on tracheal smooth muscle in rat

چکیده: زمینه و هدف: بررسی اثر عوامل تاثیر گذار بر فعالیت انقباضی عضلات صاف نای می تواند گامی در جهت کنترل بیماری های انسدادی ریوی باشد. این پژوهش با هدف بررسی اثر عصاره آبی ریشه ختمی بر فعالیت انقباضی نای جدا شده موش صحرایی انجام شده است. روش بررسی: این مطالعه تجربی روی 30 قطعه نای (mm 5) جدا شده از 15 راس موش صحرایی نر سالم در 6 گروه (5 قطعه ای) انجام شد. اثر عصاره آبی (µg/ml 6/14، 8، 6/6، 6/2، 6/0، 2/0)، اپی نفرین (mµ 5) و پروپرانولول (mµ1) بر تغییر قدرت انقباض ناشی از کلرور پتاسیم (M m60) به روش ایزومتریک تحت کشش یک گرم در حمام بافت حاوی محلول کربس- هانسلیت اندازه گیری شد. برای مقایسه داده ها از آزمون های کروسکال والیس و تعقیبی دان استفاده شد. یافته ها: غلظت های تجمعی عصاره آبی ریشه ختمی (µg/ml 6/14، 6/6، 6/2، 6/0، 2/0) به صورت وابسته به غلظت و اپی نفرین به تنهایی انقباض نای ناشی از کلرور پتاسیم را کاهش داد (001/0

Meta-analysis of the effectiveness of distance education in higher Education learning-teaching activities

Background and Objective:Higher education has faced many challenges and issues during the last two decades, among which we can mention the following: inability to produce theoretical knowledge and use of basic and theoretical knowledge produced in other countries. Of the world, the inapplicability of university education, the lack of an inappropriate relationship between the university and other social sectors, neglecting research functions and services in universities, the problem of multiple decision centers and the existence of multiple trustees on the one hand, and the excalating growth of students and applicants to universities and institutions of higher education, the slight expansion of the higher education system regardless of the existing capacity and economic, social and cultural capacity of the community to accept university graduates, reduced financial resources and pressure from society For responsibility and accountability on the other hand; the higher education system needs to maintain and improve the quality of higher education to meet these challenges. To succeed in this, all the functions of higher education in general must be considered comprehensively. In this regard, one of the measures that higher education deliberates to answer its problems was technology-based education, including distance education and distance learning. Considering the contradiction in the findings of the studies conducted on the effectiveness of distance education methods, the present study was conducted to evaluate the effectiveness of distance education in higher education. Methods: The research method is based on secondary analysis and meta-analysis. The statistical population consists of all quasi-experimental studies which have already been conducted on the effectiveness of various types of distance education in higher education in Iran. The whole census was used for sampling. According to the inclusion and exclusion criteria, 79 studies were identified as the sample size.To collect the data, a researcher-made worksheet was employed in three sections: bibliographicaldata, methodological data, and findings. To analyze the data, the effect size index and the homogeneity test were performed using CMA-Version 2.0 statistical software. Findings:The research findings indicated that all of distance education methods in higher education of Iran were effective, but this effectiveness was moderate (ES =0.526, P <0.01); the area under the normal curve, the average implementation of distance education is 69% more effective than traditional methods. In addition, the meta-regression of the effect of year on the results of research showed that with an increase in the implementation of distance education methods, .07%was added to the effectiveness of these methods. In other words, the implementation of distance education methods in higher education will become more effective over time. Conclusion: Considering that the study of moderating variables was not one of the objectives of this study, it is recommended that in future research, the impact of these components on the results of the study be examined to determine the impact of these components to explain and control the results.   ===================================================================================== COPYRIGHTS  ©2019 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.  ====================================================================================

Evaluation of physiological aspects and molecular identification of Saprolegnia isolates from rainbow trout (Oncorhynchus mykiss) and Caspian trout (Salmo trutta caspius) eggs based on RAPD–PCR

The genus of saprolegnia is one of the most important pathogenic aquatic fungi in farmed and wild fish. In the present study, fungal infected egss were collected from rainbow trout (Oncorhyncus mykiss) and Caspian trout (Salmo trutta caspius). After purification, 16 isolates were obtained (8 isolates from rainbow trout and 8 isolates from Caspian salmon, respectively). The isolates were then coded as R2 – R9 (rainbow trout) and S2 – S9 (Caspian trout).The registered DNA for S. parasitica (ACTT # 200048) and S. diclina (ACTT # 4206) were used and coded as R1 and S1, respectively. Based on the RAPD profile obtained all samples were divided to 3 groups and members of each group had more than 90% similarity among themselves. According to matrix of similarity and reference strains, the isolates were classified as three groups. Therefore, all of isolates in group 1 and 3 were S. parasitica and S. diclina, respectively, and the members of group 2 were known as Saprolegnia sp. The results of thermal resistance assessment showed that the isolates of rainbow trout and Caspian salmon eggs had slow growth in the temperature between 18 – 20 °C. Thus, R2 and S8 isolates had the lowest radial growth compared to other isolates. The isolates categorized in S. parasitica (group 1) created secoundry zoospores but not observed in two other groups. Thus, catenulated gamme was found in 78% and 55.55% isolates of rainbow trout and Caspian trout eggs, respectively. This study indicated that molecular methods were the best methods for identification of Saprolegnia spp. and it could be applied as a supplementary confirming method

Effects of different dietary levels of AFB1 on survival rate and growth factors of Beluga (Huso huso)

In the present study, the impacts of various concentrations of Aflatoxin B1 (AFB1) on Beluga, Huso huso, under controlled conditions were investigated. Belugas (120±10g) were fed on diets containing 0, 25, 50, 75, and 100 ppb AFB1/kg of diet for 3 months. Results showed various levels of AFB1 do not significantly affect the specific growth ratio (SGR) (P<0.05) of fish in different treatments. However, weight gain and food conversion ratio (FCR) were varied significantly (P<0.05 between control and treatments with diets contaminated with 75 and 100 ppb AFB1/kg after 90 days). The increase AFB1 level of did not affect on the percent of survival rate (SR) and no mortality was observed in treatments (SR=100%) suggesting that various AFB1 levels under experimental conditions of the present study affect some growth factors, such as, weight gain and FCR but have no significant impact on SR and SGR. Histopathological studies showed that different level of AFB1 can cause broad range of change in liver tissue, including progressive fat deposition, hepatocyte degeneration and necrosis, particularly at concentration of 75 and 100 ppb AFB1/kg of diets after 60 days

Spatial inequalities in the incidence of colorectal cancer and associated factors in the neighborhoods of Tehran, Iran: Bayesian spatial models

Objectives: The aim of this study was to determine the factors associated with the spatial distribution of the incidence of colorectal cancer (CRC) in the neighborhoods of Tehran, Iran using Bayesian spatial models. Methods: This ecological study was implemented in Tehran on the neighborhood level. Socioeconomic variables, risk factors, and health costs were extracted from the Equity Assessment Study conducted in Tehran. The data on CRC incidence were extracted from the Iranian population-based cancer registry. The Besag-York-Mollié (BYM) model was used to identify factors associated with the spatial distribution of CRC incidence. The software programs OpenBUGS version 3.2.3, ArcGIS 10.3, and GeoDa were used for the analysis. Results: The Moran index was statistically significant for all the variables studied (p<0.05). The BYM model showed that having a women head of household (median standardized incidence ratio SIR, 1.63; 95% confidence interval CI, 1.06 to 2.53), living in a rental house (median SIR, 0.82; 95% CI, 0.71 to 0.96), not consuming milk daily (median SIR, 0.71; 95% CI, 0.55 to 0.94) and having greater household health expenditures (median SIR, 1.34; 95% CI, 1.06 to 1.68) were associated with a statistically significant elevation in the SIR of CRC. The median (interquartile range) and mean (standard deviation) values of the SIR of CRC, with the inclusion of all the variables studied in the model, were 0.57 (1.01) and 1.05 (1.31), respectively. Conclusions: Inequality was found in the spatial distribution of CRC incidence in Tehran on the neighborhood level. Paying attention to this inequality and the factors associated with it may be useful for resource allocation and developing preventive strategies in at-risk areas. Copyright © 2018 The Korean Society for Preventive Medicine

Modelling Temperature Variation of Mushroom Growing Hall Using Artificial Neural Networks

The recent developments of computer and electronic systems have made the use of intelligent systems for the automation of agricultural industries. In this study, the temperature variation of the mushroom growing room was modeled by multi-layered perceptron and radial basis function networks based on independent parameters including ambient temperature, water temperature, fresh air and circulation air dampers, and water tap. According to the obtained results from the networks, the best network for MLP was in the second repetition with 12 neurons in the hidden layer and in 20 neurons in the hidden layer for radial basis function network. The obtained results from comparative parameters for two networks showed the highest correlation coefficient (0.966), the lowest root mean square error (RMSE) (0.787) and the lowest mean absolute error (MAE) (0.02746) for radial basis function. Therefore, the neural network with radial basis function was selected as a predictor of the behavior of the system for the temperature of mushroom growing halls controlling system

Relationship between urbanization and cancer incidence in Iran using quantile regression

Quantile regression is an efficient method for predicting and estimating the relationship between explanatory variables and percentile points of the response distribution, particularly for extreme percentiles of the distribution. To study the relationship between urbanization and cancer morbidity, we here applied quantile regression. This cross-sectional study was conducted for 9 cancers in 345 cities in 2007 in Iran. Data were obtained from the Ministry of Health and Medical Education and the relationship between urbanization and cancer morbidity was investigated using quantile regression and least square regression. Fitting models were compared using AIC criteria. R (3.0.1) software and the Quantreg package were used for statistical analysis. With the quantile regression model all percentiles for breast, colorectal, prostate, lung and pancreas cancers demonstrated increasing incidence rate with urbanization. The maximum increase for breast cancer was in the 90th percentile (β=0.13, p-value < 0.001), for colorectal cancer was in the 75th percentile (β=0.048, p-value < 0.001), for prostate cancer the 95th percentile (β=0.55, p-value < 0.001), for lung cancer was in 95th percentile (β=0.52, p-value=0.006), for pancreas cancer was in 10th percentile (β=0.011, p-value < 0.001). For gastric, esophageal and skin cancers, with increasing urbanization, the incidence rate was decreased. The maximum decrease for gastric cancer was in the 90th percentile(β=0.003, p-value < 0.001), for esophageal cancer the 95th (β=0.04, p-value=0.4) and for skin cancer also the 95th (β=0.145, p-value=0.071). The AIC showed that for upper percentiles, the fitting of quantile regression was better than least square regression. According to the results of this study, the significant impact of urbanization on cancer morbidity requirs more effort and planning by policymakers and administrators in order to reduce risk factors such as pollution in urban areas and ensure proper nutrition recommendations are made. © 2016, Asian Pacific Journal of Cancer Prevention