Motion correction of fMRI data is a widely used step prior to data analysis. In this study, a comparison of the motion correction tools provided by several leading fMRI analysis software packages was performed, including AFNI, AIR, BrainVoyager, FSL, and SPM2. Comparisons were performed using data from typical human studies as well as phantom data. The identical reconstruction, preprocessing, a...

We discuss software packages for solving optimization problems, focusing on fundamental software that assumes that the problemhas already been formulated in mathematical terms. Such packages can be used directly in many applications, linked to modeling languages or to graphical user interfaces, or embedded in complex software systems such as logistics and supply chain management systems.

Performance comparison of functional Magnetic Resonance Imaging (fMRI) software tools is a very difficult task. In this paper, a framework for comparison of fMRI analysis results obtained with different software packages is proposed. An objective evaluation is possible only after pre-processing steps that normalize input data in a standard domain. Segmentation and registration algorithms are im...

increasing competitiveness between software companies , that stems from customer needs and new information technologies, obliges the companies to improve their products’ quality according to high speed and low cost. this research seeks to introduce and determine the software production assembly line, one of the software development approaches. a three stage questionnaire was used to collect inf...

in this research, attention is focused on the resistantance of packages containing silver nanoparticles to gases such as oxygen as well as to the antimicrobial property of these packages. the effect of these packages on increasing quality and shelf time of the barberry was investigated in comparison with the current polyethylene packages. to do this, different microbial factors and the color of...

Analysis of functional magnetic resonance imaging (fMRI) data is becoming ever more computationally demanding as temporal and spatial resolutions improve, and large, publicly available data sets proliferate. Moreover, methodological improvements in the neuroimaging pipeline, such as non-linear spatial normalization, non-parametric permutation tests and Bayesian Markov Chain Monte Carlo approach...