The unparalleled rate in population explosion and advancements in technology has created alarming impacts on the society. This has urged the need for vigilant and efficient data mining of these phenomena. Petroleum being an indispensible part of life has escorted to several detrimental results. Air and water are the major elements which fall prey to this. The present study involves rigorous scrutinizing with statistical analysis of test data carried out on water samples collected from petrol pumps and automobile service stations for the determination of nature of configuration. The samples were collected at regular time intervals and at the fixed place irrespective of the weather and climatic conditions that prevailed. The haphazardness or fuzziness of the amount of contamination present in water recipients due to petroleum products is being evaluated using regression analysis and the runs test. It is found that organic and inorganic chemicals are more in the collected sample that leads to chemical oxygen demand (COD) and the same was reduced using activated rice husk as an adsorbent. A case study involving its harmful effects on concrete is accessed via Scanning Electron Microscope (SEM) tests.

In this paper, a novel method based on online monitoring of Instantaneous Exciting Current Space Phasor is presented in order to detect inter-turn faults on the transformer windings. This approach detects winding faults by comparison between presentation of the Instantaneous Exciting Current Space Phasor under healthy and faulty condition. In this work, the angular speed of Instantaneous Exciting Current Space Phasor has been introduced as one of the fault detection tools that has good sensitivity for detection of minor inter-turn faults. Firstly, a typical transformer is simulated based on Finite Element Analysis (FEA) to investigate the transformer behavior under different conditions. Then, the accuracy and performance of proposed diagnosis technique are studied by applying it to the simulated transformer.

This paper proposes a new fuzzy multi-objective optimization approach to solve a multi-objective nonlinear programming problem in context of a structural design. We have been developed a multi-objective structural problem of a planar truss structural model in fuzzy environment. Here, the objectives are (i) to minimize weight of the structure and (ii) to minimize the vertical deflection at loading point. In this model, the design variables are the cross-section of the truss members and the constraints are the stresses in members. This approach is used to solve the structural model under uncertainty based on different operator. A numerical illustration is given to support our approach.