application of satellite imagery and remote sensing techniques in agriculture and other natural resources has been approved by many studies. in this study two etm+ imagery data for may and september 2012 of astan ghods razavi great farm were acquired to identify the boundaries of lands cultivated with different crops coverage and to create crops maps of that farm. . to classify the images, the ...

the aim of this study was to propose a method for improving the power of recognition and classification of thromboembolic syndrome based on the analysis of ‎ gene expression data using artificial neural networks. the studied method was performed on a dataset which contained data about 117 patients admitted to a hospital in durham in 2009. of all the studied patients, 66 patients were suffering ...

this study investigates the detection of the drowsiness state for a future application such as in the reduction ofthe road traffic accidents. the electroencephalography(eeg), electrooculography (eog), driving quality (dq), and karolinska sleepiness scale (kss) data of 7 male during approximately 20 hours of sleep deprivation were recorded. to reduce the eye blink artifact, an automatic mechanis...

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...

the major aim of processing satellite images is to prepare topical and effectivemaps. the selection of appropriate classification methods plays an important role. amongvarious methods existing for image classification, artificial neural network method is ofhigh accuracy. in present study, tm images of 1987, and etm+ images of 2000 and 2006were analyzed using artificial fuzzy artmap neural netwo...

Network embedding is a highly effective method to learn low-dimensional node vector representations with original network structures being well preserved. However, existing algorithms are mostly developed for single network, which fail generalized feature across different networks. In this paper, we study cross-network classification problem, aims at leveraging the abundant labeled information ...

Fast and accurate network traffic identification is becoming essential for network management, high quality of service control and early detection of network traffic abnormalities. Techniques based on statistical features of packet flows have recently become popular for network classification due to the limitations of traditional port and payload based methods. In this paper, we propose a metho...

breathomics is the metabolomics study of exhaled air. it is a powerful emerging metabolomics research field that mainly focuses onhealth-related volatile organic compounds (vocs). since the quantity of these compounds varies with health status, breathomics assuresto deliver noninvasive diagnostic tools. thus, the main aim of breathomics is to discover patterns of vocs related to abnormal metabo...