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In the domain of bioinformatics, the clustering of gene expression profiles of different tissue samples over different experimental conditions has gained importance with the invention of micro-array based technology. This study also has some impact on cancer diagnosis. The proper classification of cancer tissue samples generated using the micro-array technology helps in detecting cancers in an automated way. In the current paper we have developed a semi-supervised clustering technique for proper partitioning of these gene expression data sets. Semi-supervised clustering is a combination of unsupervised and supervised classification techniques. It uses some amount of supervised information and a large collection of unsupervised data. Here a multi-objective based semi-supervised clustering technique is developed for solving the cancer tissue classification problem. Different combinations of objective functions are used. As the supervised information we assume that class labels of 10 % data are available. The proposed technique is evaluated for three open source benchmark cancer data sets (brain tumor data set, adult malignancy and small round blood cell tumors). Two classification quality measures, viz., Adjusted Rand Index and Classification Accuracy are used to measure the goodness of the obtained partitionings. Obtained results are compared with several state-of-the-art clustering techniques. Moreover, significant gene markers have been identified and demonstrated visually from the clustering solutions obtained.

This piece of work aims at the modeling and using the finite element method approach (FEM) to analyze the fatigue behavior of bolted beam to column end-plate connection in the structural steel framework subjected to static loading. A detailed three dimensional (3D) simulation model of the bolted beam to column end-plate connection is constructed in PRO-E wildfire and it is analyzed in the ANSYS workbench to obtain its behavior. The bolted end-plate connection is chosen as an important type of beam to column joint. The end-plate connection is chosen for its complexity in the analysis and behavior due to the number of connection components and their inheritable behavior. The solid elements, bonded contact and the bolt pretension are included to obtain the behavior of the structure. The FEA results of the structure with or without bolt pretension are compared with the available literature. At last the fatigue behavior of connections under over tensioning is presented in this work.

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Abstract-The asymmetry phenomenon observed during the load-loss test of three-phase transformers is rigorously analyzed. The transformer is represented as a three-port impedance network despite its six-port network nature, making any formal study more tractable. The analytical restrictions required for such a representation are derived. As a result, it is possible to mathematically prove (and understand) the asymmetrical behavior of a three-phase transformer subjected to the load-loss test. Only two circuit-field simulations or tests (single-phase load-loss tests) are required to obtain the impedance system of the six-winding transformer. A 3-D finite-element (FE) model of a transformer is used here to obtain its short-circuit impedances, exemplifying the use and extent of the analytical results. The eddy currents generated at the transformer tank and frame are properly taken into consideration. The short-circuit impedance model is validated with the 3-D FE model and with a six-port network approach that has been previously verified.Index Terms-Asymmetry phenomenon, finite-element models (FEMs), network models, short-circuit impedances.