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In this study, the non-dominated sorting genetic algorithm (NSGA-II) is used for the multi-objective optimization of the Sefidrud reservoir in Northern Iran. The main objectives include water supply, hydropower generation and sediment flushing. In addition to some physical constraints such as the reservoir storage and the outlet flow, maximum flushing outflow and non-flushing in irrigation seasons, the environmental constraints as fish migration and spawning are taken into an account. After obtaining the Pareto optimal solutions by means of the weighted objective functions and non-symmetric Nash bargaining, various scenarios are defined. Then these scenarios are analyzed by introducing a new sustainability index. Furthermore, the different percentages of downstream water demand are considered in order to achieve a better evaluation of the scenarios. The results of study indicate that the optimal solutions are more sustainable than those of the current operation of Sefidrud reservoir, which increase the sediment flushing by 37 million tons compared to the current operation, with the same hydroelectric energy and downstream water supply. The proposed methodology could be used successfully in other reservoir operations including the sediment flushing. [ABSTRACT FROM AUTHOR]

Background: Liver cirrhosis was one of the most important liver diseases. Other chronic liver diseases could be lead to liver cirrhosis. Liver cirrhosis could be lead one kind of liver cancers named hepatocellular carcinoma. Cirrhosis in the early stages just by laboratory and imaging testes could be diagnosed. In this study cirrhotic patients were classified based on laboratory symptoms. For this purpose data mining approach has been used in this research. Data mining was an interdisciplinary science that discovers the hidden knowledge in the data. Materials and Methods: We used K-Means algorithm to categorize the statues of cirrhotic patients. In order to determine the quality of clustering results and to find the best number of clusters, we have used silhouette indices. Results: Our data consists of 410 records which have been collected from Dr. Shariati hospital The number of features in this study are .1 items and sampling were divided into two main groups. Conclusion: At first, we have done clustering based on 21 attributes and the average silhouette was 41 percent. We improved the model, in order to reach a reasonable structure. Finally, based on 7 attributes, a reasonable clustering model was derived. The new model provides 64 percent average silhouette, and based on patients' status, patients are divided into 2 main categories. The risk of HCC in the first cluster is 23 percent and in the second cluster is 14 percent. [ABSTRACT FROM AUTHOR]

The article presents a study on the effectiveness of a heart sound segmentation algorithm with homomorphic filtering for noise reduction. Topics include the growth in the popularity of phonocardiography, heart sound analysis by auscultation, and the performance of peak conditioning. It also discusses the probability of misclassification of sounds due to extra sounds produced such as murmurs, noise from an electronic stethoscope, and heart sounds.

Prediction of daily evaporation has an important role in reservoir management, regional water planning and evaluation of drinking-water supplies. The main purpose of this study was to assess different types of mother wavelet as activation functions instead of commonly used sigmoid for finding the main differences in the results of daily pan evaporation prediction in the Lar synoptic station. So, using conjunction of wavelet theory and multilayer perceptron (MLP) network, two mother Wavelets named Mexican Hat and polyWOG1 are considered for developing hybrid WNNs. The algorithms were trained and tested using a 6-year data record (1999 daily values) from 2005/01/01 to 2010/09/01. Instead of using common sigmoid activation functions in MLP network, wavelet function was applied to construct the wavelet neural network. Results show that Mexican hat wavelet neural network in the best topology presents 98.35 % accuracy in training phase and 96.04 % in testing and PolyWOG1 wavelet neural network in the best topology presents 95.92 % accuracy in training phase and 91.03 % in testing of model. In the MLP model with standard sigmoid function results were 90.6 % in training and 87.63 % in testing. Comparison of WNN and MLP shows that Mexican hat mother wavelet could have better accuracy in the daily pan evaporation modeling. [ABSTRACT FROM AUTHOR]

Of several brick tomb towers constructed at Maragha in western Iran before the Mongol conquests, one in particular, Gonbad-e Qabud (593 H. / 1196-97 C.E.), has generated significant recent attention for its unique patterns with pentagons and decagons. Gonbad-e Qabud is also unusual in having a decagonal plan. While both plan and decoration distinguish it from earlier and later towers at Maragha and elsewhere on the Iranian plateau, the ornamental patterns follow a long line of experimentation with geometric expressions that grace many pre-Mongol buildings in Iran. This article examines in particular the overlapping polygons and radial symmetries of the tympanum of the cubic Gonbad-e Sork (542 H. / 1148 C.E.) at Maragha, and the pentagons and squares of the tympanum of the later octagonal tomb tower (486 H. / 1093 C.E.) nearby at Kharraqan. Drawing from archival sources (plans, elevations, photographs), analysis of plane patterns, and comparative architectural data, this article reevaluates the cultural significance of Gonbad-e Qabud, seeking to situate it within the histories of mathematics, architecture, and the arts. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is one of the most prevalent cancers among women today. The importance of breast cancer screening, its role in the timely identification of patients, and the reduction in treatment expenses are considered to be among the highest sanitary priorities of a modern country. Thermal imaging clearly possesses a special role in this stage due to rapid diagnosis and use of harmless rays. Methods: We used a thermal camera for imaging of the patients. Important parameters were derived from the images for their posterior analysis with the aid of a genetic algorithm. The principal components that were entered in a fuzzy neural network for clustering breast cancer were identified. Results: The number of images considered for the test included a database of 200 patients out of whom 15 were diagnosed with breast cancer via mammography. Results of the base method show a sensitivity of 93%. The selection of parameters in the combination module gave rise measured errors, which in training of the fuzzy-neural network were of the order of clustering 1.0923x10-5, which reached 2%. Conclusion: The study indicates that thermal image scanning coupled with the presented method based on artificial intelligence can possess a special status in screening women for breast cancer due to the use of harmless non-radiation rays. There are cases where physicians cannot decisively say that the observed pattern in the image is benign or malignant. In such cases, the response of the computer model can be a valuable support tool for the physician enabling an accurate diagnosis based on the type of imaging pattern as a response from the computer model. [ABSTRACT FROM AUTHOR]

The article presents a study which examined the novel shapes and texture features that can be effectively used to classify benign and malignant breast cancer masses in sonography images. Also cited are the six features that were extracted including eccentricity, solidity, and cross-correlation, as well as the most common methods used for breast cancer diagnosis like self-examination, sonography and mammography.

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Reservoir system reliability is the ability of reservoir to perform its required functions under stated conditions for a specified period of time. In classical method of reservoir system reliability analysis, the operation policy is used in a simple simulation model, considering the historical/synthetic inflow series and a number of physical bounds on a reservoir system. This type of reliability analysis assumes a reservoir system as fully failed or functioning, called binary state assumption. A number of researchers from various research backgrounds have shown that the binary state assumption in the traditional reliability theory is not extensively acceptable. Our approach to tackle the present problem space is to implement the algorithm of advance first order second moment (AFOSM) method. In this new method, the inflow and reservoir storage are considered as uncertain variables. The mean, variance and covariance of uncertain variables are determined using moment values of reservoir state variables. For this purpose, a stochastic optimization model developed based on the constraint state formulation is applied. The proposed model of reliability analysis is used to a real case study in Iran. As a result, monthly probabilities of water allocation were computed from AFOSM method, and the outputs were compared with those from Monte Carlo method. The comparison shows that the outputs from AFOSM method are similar to those from the Monte Carlo method. In term of practical use of this study, the proposed method is appropriate to determine the monthly probability of failure in water allocation without the aid of simulation. [ABSTRACT FROM AUTHOR]

We present the first detailed source model of the 1997 M7.2 Zirkuh earthquake that ruptured the entire Abiz fault in East Iran producing a 125 km long, bended and segmented fault trace. Using SAR data from the ERS and JERS-1 satellites we first determined a multisegment fault model for this predominately strike-slip earthquake by estimating fault-segment dip, slip, and rake values using an evolutionary optimization algorithm. We then inverted the InSAR data for variable slip and rake in more detail along the multisegment fault plane. We complement our optimization with importance sampling of the model parameter space to ensure that the derived optimum model has a high likelihood, to detect correlations or trade-offs between model parameters, and to image the model resolution. Our results are in an agreement with field observations showing that this predominantly strike-slip earthquake had a clear change in style of faulting along its rupture. In the north we find that thrust faulting on a westerly dipping fault is accompanied with the strike-slip that changes to thrust faulting on an eastward dipping fault plane in the south. The centre part of the fault is vertical and has almost pure dextral strike-slip. The heterogeneous fault slip distribution shows two regions of low slip near significant fault step-overs of the Abiz fault and therefore these fault complexities appear to reduce the fault slip. Furthermore, shallow fault slip is generally reduced with respect to slip at depth. This shallow slip deficit varies along the Zirkuh fault from a small deficit in the North to a much larger deficit along the central part of the fault, a variation that is possibly related to different interseismic repose times. [ABSTRACT FROM AUTHOR]

Because compressed gas is a scarce and expensive resource, allocating an optimal amount of gas injection to a group of wells to increase the oil production rate is an important optimization problem in the gas lift operation. In this article, a particle swarm optimization algorithm is employed to assign an optimum gas injection rate for each individual well. Also, a new gas lift performance curve-fit that can reduce the time and volume of the computation is suggested. Finally, the algorithm is tested on five wells in an Iranian oil field. [ABSTRACT FROM AUTHOR]

The sequences of 16S rDNA, cytochrome oxidase subunit I ( COI) and cytochrome b ( Cyt b) genes from nine field collections (seven provinces in China: Guangxi, Hubei, Guangdong, Guizhou, Zhejiang, Hunan, Jiangxi, and also southern and northern part of Iran), plus the sequences of Africa, Europe, Americas and Japan obtained form GenBank were used to re-analyse the genetic variation in the southern green stink bug Nezara viridula (Linnaeus). The phylogeographic re-analysis by using four algorithms (NJ, MP, ML and Bayesian) showed three main lineages. The Iranian haplotypes fell into lineage II formed from Europe and America, rather than in lineage III from Asia; the Chinese haplotypes fell into the Asian clade. Our results suggested that African and non-African gene pools have been isolated since the Miocene era with the molecular clock calibrations for Heteroptera mtDNA, and not since the Pliocene as mentioned previously. The corresponding age of the separation of the eastern and western Asia clades is estimated to be 4.0-1.6 million years ago, coinciding with the Pliocene-Pleistocene epoch and with acute rising events in the Tibet Plateau locates in the western China, which may have formed the barriers observed today. [ABSTRACT FROM AUTHOR]

A neural network combined to an artificial neural network model is used to forecast daily total atmospheric ozone over Isfahan city in Iran. In this work, in order to forecast the total column ozone over Isfahan, we have examined several neural networks algorithms with different meteorological predictors based on the ozone-meteorological relationships with previous day’s ozone value. The meteorological predictors consist of temperatures (dry and dew point) and geopotential heights at standard levels of 100, 50, 30, 20 and 10 hPa with their wind speed and direction. These data together with previous day total ozone forms the input matrix of the neural model that is based on the back propagation algorithm (BPA) structure. The output matrix is the daily total atmospheric ozone. The model was build based on daily data from 1997 to 2004 obtained from Isfahan ozonometric station data. After modeling these data we used 3 year (from 2001 to 2003) of daily total ozone for testing the accuracy of model. In this experiment, with the final neural network, the total ozone are fairly well predicted, with an Agreement Index 76%. [ABSTRACT FROM AUTHOR]

Two adaptive extensions of the varying chromosome length genetic algorithm (VLGA) model are proposed for optimal reservoir operation. The initial solutions for each year of the planning horizon are selected among the optimal solutions for the previous years based on the similarity in hydrologic characteristics of the years in terms of reservoir storage at the beginning of water years and annual reservoir inflows. The results from three case studies in Iran show an improvement in the convergence speed of VLGA between 21-47%. In an extended time horizon problem, the models improve the best fitness values with significantly less computation. [ABSTRACT FROM AUTHOR]

Abstract Optimization of a multi-reservoir system operation is challenging due to the non-linearity, stochasticity, and dimensionality involved in such a problem. In this research, a long-term planning model is presented for optimizing the operation of Iranian Karoon-Dez reservoir system using an interior-point algorithm. The system is the largest multi-purpose reservoir system in Iran with hydropower generation, water supply, and environmental objectives. The focus is on resolving the dimensionality of this problem while considering hydropower generation and water supply objectives. The weighting and constraints methods of multi-objective programming are used to assess the trade-off between water supply and hydropower objectives so as to find noninferior solutions. The computational efficiency of the proposed approach is demonstrated using historical data taken from Karoon-Dez reservoir system. [ABSTRACT FROM AUTHOR]

Presents an algorithm for long-term operation of hydrothermal power systems in Iran. Details of the hydrothermal coordination problem; Factors considered in long-tern optimization of hydrothermal resources; Formulation of the problem of hydrothermal plants.

This study focuses on development of equilibrium strategy based on simulated annealing (SA) algorithm for balancing economic and environmental concerns in waste load allocation (WLA) problem. To resolve conflicts among various stakeholders, including Iran Department of Environment (DoE) as governmental authority and industrial and municipal dischargers, Stackelberg and Nash bargaining games have been applied in this WLA problem and the results have been compared. SA algorithm has been coupled to QUAL2Kw model to derive optimal WLA program and the environmental penalty tariff (EPT) in Nash bargaining and Stackelberg games. The proposed tools and methodologies were illustrated in a case study of multi-stakeholders WLA problem in Gheshlagh River, Sanandaj, Kordestan, Iran. The results indicate that lower BOD removal rates are allocated to the pollutant dischargers in the Stackelberg game compared to the Nash bargaining game. Furthermore, the EPT assigned by Iran DoE in Stackelberg and Nash bargaining games are 11.25 and 3.6 Rials/(gr/month), respectively. The estimated EPT in the Stackelberg game is close to the current tariff (10 Rials/(gr/month)) specified by Iran DoE on impermissible BOD discharges. [ABSTRACT FROM AUTHOR]