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Friction Stir Welding (FSW) is employed for welding the metal surfaces without changing their phase. The major process variables of FSW are the profile of tooltip including plain or grooved surfaces, rotary speed of the tooltip, the angle of the tool fixed, and the vertical force on the tooltip. This investigation focuses the tooltip geometry with plain surface in FSW of AA6061. Initially conventional cylindrical profile is considered with a predefined tool spinning speed of the tool and compressive force which applied over it axially, for a specific welding application. The factors varied four levels. The stability related, thermal, and transient investigations were performed. The observations were compared with different geometries including two different truncated cone profiles and a hexagonal prismatic profile. The best profile suggested based on the investigation results.

In this paper, A High Gain Low Power Operational Amplifier was designed in main for the usage of in biomedical applications. The amplifier is designed to produce high gain with less power consumption. The PMOS input transistors are used with high gate areas which operate in subthreshold or cutoff region helps in reduction of flicker noise. Later switched bias is used to further reduce noise levels by making input transistors switch between cutoff and inversion regions. This switched bias helps in reduction of noise with less power, thus helps in low power usage in reduction of noise. The supply voltage is ±1.5V with average gain of the amplifier is 87dB in required frequency range and CMRR of about 128dB. The unity gain frequency is 5.3MHz and cutoff frequency is 43.6KHz. Average power consumption of the model is 24.8μW. The model is designed using TSMC-180nm process, in the S-Edit of Tanner EDA. The simulations are carried under different temperatures i.e. 25o,36.9o (body temperature) and 40o. This amplifier is intended to amplify neural spikes which are in low amplitudes(mV) and in frequency range of about 5-100Hz.

A two stage noise reduction approach is proposed in this paper. This paper focuses on Wiener filter based single channel speech enhancement method. First stage consists of Gamma tone filtering method for sub banding and synthesizing; perceptualWiener filter is used to apply gain function on each sub band to reduce the noise at each critical frequency. Performance of perceptual Wiener filter is improved by finding self adaptive averaging factor to estimate a priori SNR. To reduce residual musical noise that remains in the enhanced speech, perceptual weighting filter is developed based on simultaneous and temporal masking effects of human auditory system is used as a second stage in the proposed system. An unvoiced speech enhancement algorithm is also integrated into the system to improve the intelligibility of speech. Through rigorous objective and subjective evaluations, it is shown that the proposed speech enhancement system is capable of reducing noise with little speech distortion in adverse noise environments and overall performance is superior to several competitive methods.