Multiobjective Optimal Water ResourcesManagement for a Large River Basin

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CT Brain Image: Abnormalities Recognition and Segmentation

In order to develop an automated segmentation system for Computed Tomography (CT) brain images, a new approach which consists of several unsupervised segmentation techniques was introduced. The system segments the CT brain images into three partitions, i. e., abnormalities, cerebrospinal fluid (CSF), and brain matter. Our approach consists of two phase-segmentation methods. In the first phase segmentation, k-means and fuzzy c-means (FCM) methods were implemented to segment and transform the images into the binary images. Based on the connected component in binary images, a decision tree was employed for the annotation of normal or abnormal regions, In the second phase segmentation, the modified FCM with population-diameter independent (PDI) segmentation was applied to segment the images into CSF and brain matter. The experimental results have shown that our proposed system is feasible and yield satisfactory results.     

Cu-Zn-Al2O3 nanocomposites: study of microstructure,corrosion, and wear properties

Alumina nanoparticles were added to a Cu-Zn alloy to investigate their effect on the microstructural, tribological, and corrosion properties of the prepared alloys. Alloying was performed using a mixture of copper and zinc powders with 0vol% and 5vol% of α-Al nanopowder in a satellite ball mill. The results showed that the Cu-Zn solid solution formed after 18 h of mechanical alloying. The mechan-ically alloyed powder was compacted followed by sintering of the obtained green compacts at 750℃ for 30 min. Alumina nanoparticles were uniformly distributed in the matrix of the Cu-Zn alloy. The tribological properties were evaluated by pin-on-disk wear tests, which revealed that, upon the addition of alumina nanoparticles, the coefficient of friction and the wear rate were reduced to 20% and 40%, respectively. The corrosion properties of the samples exposed to a 3.5wt% NaCl solution were studied using the immersion and potentiodynamic polarization methods, which revealed that the addition of alumina nanoparticles reduced the corrosion current of the nanocomposite by 90%.     

Application of SSM in tackling problematical situations from academicians’ viewpoints

In recent years, a wide variety of studies have applied soft systems methodology (SSM) to address the complexities of the messy situations. This paper seeks to identify 1) application areas and 2) application levels of the use of SSM in dealing with problematical situations. To do so, 149 articles published between 2000 and 2015 were studied. The findings revealed the application of SSM in new application areas such as sustainable development, knowledge management and project management. The results of this study also indicated that researchers applied SSM at three levels: SSM as a process of inquiry, SSM as an action-oriented methodology, and the hybrid use of SSM. Based on the findings, SSM at the level of a single methodology for bringing out changes has been less welcomed by researchers, but the application levels of inquiry processes and hybrid approaches have been more utilized. This suggests that in the correspondence of SSM with the nature or situation of problems, a sort of incommensurability is witnessed. Factors arising from the nature of the problem, inadequate mastery of the researcher over SSM or the limitations of SSM can exert an influence on this incommensurability.     

A data-mining approach to biomarker identification from protein profiles using discrete stationary wavelet transform

Objective： To develop a new bioinformatic tool based on a data-mining approach for extraction of the most informative proteins that could be used to find the potential biomarkers for the detection of cancer. Methods： Two independent datasets from serum samples of 253 ovarian cancer and 167 breast cancer patients were used. The samples were examined by surfaceenhanced laser desorption/ionization time-of-flight mass spectrometry （SELDI-TOF MS）. The datasets were used to extract the informative proteins using a data-mining method in the discrete stationary wavelet transform domain. As a dimensionality reduction procedure, the hard thresholding method was applied to reduce the number of wavelet coefficients. Also, a distance measure was used to select the most discriminative coefficients. To find the potential biomarkers using the selected wavelet coefficients, we applied the inverse discrete stationary wavelet transform combined with a two-sided t-test. Results： From the ovarian cancer dataset, a set of five proteins were detected as potential biomarkers that could be used to identify the cancer patients from the healthy cases with accuracy, sensitivity, and specificity of 100%. Also, from the breast cancer dataset, a set of eight proteins were found as the potential biomarkers that could separate the healthy cases from the cancer patients with accuracy of 98.26%, sensitivity of 100%, and specificity of 95.6%. Conclusion： The results have shown that the new bioinformatic tool can be used in combination with the high-throughput proteomic data such as SELDI-TOF MS to find the potential biomarkers with high discriminative power.     

Fabrication and characterization of nanocrystalline Al/Al12（Fe,V）3Si alloys by consolidation of mechanically alloyed powders

The aim of this study was to produce bulk nanocrystalline Al/Al12（Fe,V）3Si alloys by mechanical alloying （MA） and subsequent hot pressing （HP） of elemental powders. A nanostructured Al-based solid solution was formed by MA of elemental powders for 60 h. After HP of the as-milled powders at 550℃ for 20 min, the Al12（Fe,V）3Si phase was precipitated in a nanocrystalline Al matrix. Scanning electron microscopy （SEM） images of the bulk samples represented a homogeneous and uniform microstructure that was superior to those previously obtained by rapid solidification-powder metallurgy （RS-PM）. Nanostructured Al-8.5Fe-1.3V-1.7Si and Al-11.6Fe-1.3V-2.3Si alloys ex-hibited high HV hardness values of～205 and～254, respectively, which are significantly higher than those reported for the RS-PM counter-parts.     

Influence of the roughness and shape of quartz particles on their flotation kinetics

Surface roughness and shape play an important role on the behavior of particles in various processes such as flotation. In this research, the influence of different grinding methods on the surface roughness and shape characteristics of quartz particles as well as the effect of these parameters on the flotation of the particles was investigated. The surface roughness of the particles was determined by measuring their specific surface area via the gas adsorption method. The shape characteristics of the particles were measured and calculated by images obtained by scanning electron microscopy via an image analysis system. The flotation kinetics was determined using a laboratory flotation cell. The results showed that the particles of rod mill products have higher roughness and elongation ratio and lower roundness than the particles of ball mill products. The flotation kinetics constant of the particles increased with their surface roughness increasing. Particles with higher elongation and lower roundness indicated higher floatability. In addition, the influence of the surface roughness on the flotation kinetics was greater than that of shape parameters.