streptokinase is a potent fibrinolytic agent which is widely used in treatment of deep vein thrombosis (dvt), pulmonary embolism (pe) and acute myocardial infarction (mi). major limitation of this enzyme is its short biological half-life in the blood stream. our previous report showed that complexing streptokinase with chitosan could be a solution to overcome this limitation. the aim of this re...

artificial neural network is one of the most robust and reliable methods in online prediction of nonlinear incidents in machining. tool flank wear as a tool life criterion is an important task which is needed to be predicted during machining processes to establish an online tool life estimation system. in this study, an artificial neural network model was developed to predict the tool wear and ...

osmotic dehydration, as a minimal processing method, has found increasingly wide prospects during the past few decades. this process involves mass transfer which is commonly modeled by applications of different procedures, mostly based on fick's law. in this research, we approached the modeling process by first obtaining experimental measurement of potato’s solid gain, water loss and moisture c...

abstract cation exchange capacity (cec) is an important characteristic of soil in terms of nutrient and water holding capacities and contamination management. measurement of cec is laborious and time-consuming. therefore, cec estimation through other easily - measured properties is desirable. in this study, ptfs for estimation of cation exchange capacity from basic soil properties such as parti...

abstract infiltration is a significant process which controls the fate of water in the hydrologic cycle. the direct measurement of infiltration is time consuming, expensive and often impractical because of the large spatial and temporal variability. artificial neural networks (anns) are used as an indirect method to predict the hydrological processes. the objective of this study was to develop ...

the main objective in classification of the nmr spectra of cancerous and healthy tissue , with high number of features is the prerequisites of the minimum number of samples. therefore the use of conventional classifier on this type of the data is not recommended. in the current work, different structures of the artificial neural networks (ann) were tried on classification of different cancerous...

artificial neural networks (ann) have shown to be a powerful tool for system modeling in a wide range of applications. the focus of this study is on neural network applications to data analysis in egg production. an ann model with two hidden layers, trained with a back propagation algorithm, successfully learned the relationship between the input (age of hen) and output (egg production) variabl...

groundwater quality management is the most important issue in many arid and semi-arid countries, including iran.artificial neural network (ann) has an extensive range of applications in water resources management. in this study,artificial neural network was developed using matlab r2013 software package, and cl, ec, so4 and no3 qualitativeparameters were estimated and compared with the measured ...

one very significant issues in most educational systems, the question is educational achievement levels of students in exams. the educational system is one of the most important indicators of education performance and evaluation of teaching and the learning is the fact that the performance of the system output in each year. the method of the research is descriptive-survey. the research communit...

background: brain tissue segmentation for delineation of 3d anatomical structures from magnetic resonance (mr) images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (gm), white matter (wm) and cerebrospinal fluid (csf), but only if the obtained segmentation results are correct. due to image arti...