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A self-guided automated robot is basically a robot designed to follow a line or path which is already pre-determined by the user. The main focus of this report is to design a selfguided automated path following robot which is more reliable by eliminating the demerits of the traditionally used robots by the idea of making it a magnetic field line following robot. This paper presents the principle of a magnetic field line following robot and also explains its design and working. Here, the design of a self-guided automated magnetic field line following robot using LC tank circuits and resonant coupling for navigation purposes is explained. Also this paper gives the idea of a path that can be made invisible and can be buried under the ground and also focuses on the various electrical circuitries involved in this self-guided automated magnetic field line following the robot. This paper discusses all the components that are used in this self-guided automated vehicle. The applications and the advantages of this self-guided automated magnetic field line following robot over the traditional path following robots are discussed along with the future upgradations that can be done to refine it further.

Bioanalysis of an endogenous compound such as leucovorin is never an easy task on a liquid chromatography tandem mass spectrometer (LC-MSMS). Unless it is necessary, regulatory guidance discourages working with surrogate matrices for calibration curve standard preparation. Herein, a selective and sensitive liquid chromatography-tandem mass spectrometry method for simultaneous determination of leucovorin and 5-methyl tetrahydrofolic acid in human plasma was developed and validated. Stable labeled internal standards, i.e. leucovorin D

A self-guided automated robot is basically a robot designed to follow a line or path which is already pre-determined by the user. The main focus of this report is to design a self guided automated path following robot which is more reliable by eliminating the demerits of the traditionally used robots by the idea of making it a magnetic field line following robot. This paper presents the principle of a magnetic field line following robot and also explains its design and working. Here, the design of a self-guided automated magnetic field line following robot using LC tank circuits and resonant coupling for navigation purposes is explained. Also this paper gives the idea of a path that can be made invisible and can be buried under the ground and also focuses on the various electrical circuitries involved in this self-guided automated magnetic field line following the robot. This paper discusses all the components that are used in this self-guided automated vehicle. The applications and the advantages of this self-guided automated magnetic field line following robot over the traditional path following robots are discussed along with the future upgradations that can be done to refine it further.

Separating audio sources from a convolutive mixture of signals from various independent sources is a very fascinating area in personal and professional context. The task of source separation becomes trickier when there is no idea about mixing environment and can be termed as blind audio source separation (BASS). Mixing scenario becomes more complicated when there is a difference between number of audio sources and number of recording microphones, under determined and over determined mixing. The main challenge in BASS is quality of separation and separation speed and the convergence speed gets compromised when separation techniques focused on quality of separation. This work proposed divergence algorithm designed for faster convergence speed along with good quality of separation. Experiments are performed for critically determined audio recording, where number of audio sources is equal to number of microphones and no noise component is taken into consideration. The result advocates that the modified convex divergence algorithm enhance the convergence speed by 20-22% and good quality of separation than conventional convex divergence ICA, Fast ICA, JADE.

Taking assumption the hidden sources are statistically independent, Independent component analysis technique separates these sources from a linear mixture of audio signals, communication signals generated by equally spaced independent audio sources. Since, in Audio applications source exhibit non dependence. Mutual information minimization corresponds to minimization of entropy, that ensures quality of separation and exploits non-Gaussianity, noncircularity and sample dependence simultaneously. In this paper these properties are exploited with the help of Cramer-Rao lower bound, modified convex divergence based ICA, Fast ICA and JADE. The performance of these techniques are examined with the help of a number of example and a comparative analysis presented in term of failure percentage and average CPU time taken for execution. Keywords— Independent Component Analysis, Blind Source Separation, Convex Divergence, Independence, non-Gaussianity,.

A simple, rapid, and specific assay based on solid phase extraction and liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI MS-MS) for the quantitative analysis of Tenofovir in human serum using Tenofovir D6 as internal standard (IS) have been developed. The precursor to product ion transitions of m/z 288.2/176.2 and m/z 293.9/182.3 used to measure the analyte and internal standard (Tenofovir and Tenofovir D6). The method was validated over a concentration range of 5.06–603.72 ng mL −1 . The method was validated over the parameters like selectivity, matrix effect, sensitivity, linearity, precision, accuracy, various stabilities (bench top stability, standard stock solution stability in refrigerator and at room temperature, stock dilution stability, auto sampler stability, freeze thaw stability, long term stability – 65°C±10°C & long term stability – 22°C±5°C, reagent stability, dry extract stability, wet extract stability in refrigerator and at bench top, blood stability), effect of potentially interfering drugs, dilution integrity, recovery and reinjection reproducibility. The mean % recovery of Tenofovir was 98.22% with a precision of 2.42%, The mean % recovery of Tenofovir D6 was 100.96% with a precision of 2.88%. The RSD % of intra-day and inter-day assay was≤15%.

Blind audio source separation is a promising area for various applications like humanoids, human machine inter- action or adverse control mechanism, etc. ICA is a predominant approach for source separation in blind scenario. There are various versions of ICA to solve this purpose like Fast ICA, JADE, and C-ICA. The convergence speed and quality of separation is an issue. In this work a weight initialization approach is proposed for optimizing the convergence speed and experimental results reflects up to 28.57% that the proposed weight initialized ICA gives better convergence speed in comparison of Fast ICA. Here a critically determined ideal mixing system is considered where no noise component is taken into account.

Audio Source separation techniques are used for better reception of sound and speech signals. Wiener filtering tool is best and one of the principally used method in separation of the audio signal from mixture of source signals. As the STFT utilizes short-duration stationarity in time frequency domain, we use Wiener filtering mask which does not depends on the consistency of the output for the voice gram and is different from the STFT in time-frequency domain. Short-time Fourier transform (STFT) in time-frequency domain is used if processing is done on audio signals. In this paper a technique for blind audio source separation using Wiener filtering algorithm is presented and result reflects that it serves good quality of separation in comparison of classical ICA algorithms like fast ICA, JADE. So it gives the SIR value 6.68% and 39.22% higher than that of fast ICA and JADE respectively.

Acquisition is an essential building block in almost any real life data processing. In acquisition it is key target to keep aliasing low often dictates the use of a complex analog anti-aliasing filter. In case of multichannel system, each channel must be fitted with a separate anti-aliasing filter as such filter cannot be multiplexed but this exercise becomes expensive. In this paper the cost optimized structure for multiple channel data acquisition system is proposed, the cost optimization achieved by using multistage decimation. The MATLAB simulation has been used to evaluate proposed model and in result cost reduced by 53.27% when (M=16*2) has been used instead of M=32. The cost has been further reduced by 69% for combination of M=(8*4), Key targets are filter length reduction and aliasing. Finite-impulse-response (FIR) has been used for implementation of idea.