MaveraMazhar Profile

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pakistan

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Joined November 30, 2015

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MaveraMazhar

@MaveraMazhar

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pakistan

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Computer Engineer

I am a Computer Engineer and hold a Masters degree from NUST, Pakistan in Computer Engineering with specialization in Machine Learning and Pattern Recognition. I have topped the university in MS program with the highest CGPA of 4.0/4.0. I have sound expertise on sciences related subjects, user manual and content writing, academic and research paper writing, machine learning and pattern recognition, data science, MATLAB, Microsoft Office, Pidoco and many other tools. I have a sound experience in academic writing and teaching engineering students. I have various research publications in academia and also a professional experience of working in an international software house . I am very goal-oriented, persistent, highly motivated and I welcome challenges in my way!

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Education

Masters in Computer Engineering

National University of Science and Technology,

Pakistan

2013 - 2015

(2 years)

Publications

Classifying SNR and Cardiac Arrhythmias in ECG Signals Using Statistical Features in Temporal Domain

IEEE

ECG plays a vital role in diagnosis of many such cardiac disorders. Clinical analysis of ECGs by physicians may result into an inaccurate as well as a time-consuming analysis of a critically serious arrhythmia patients. Considering the importance of morphological shapes and statistics of ECG signals in arrhythmia diagnosis, these features are input to a dedicated system which act as key markers to categorize various arrhythmias automatically

IDE for generation of middleware for hybrid processors based embedded systems

IEEE

This paper presents a novel idea of hybrid processors configuration in NoS using an Integrated Development Environment (IDE) generated middleware. The user will be able to configure or reconfigure the NoS, whereas the inter-communication of hybrid processors on the NoS will take place in an abstraction layer without any user intervention. The basic model of NoS and the proposed prototype for GUI based IDE used for middleware generation have been explained in detail.

Denoising practices for electrocardiographic (ECG) signals: A survey

IEEE

Noise sources in ECG can either be cardiac or extra cardiac, resulting in the distribution of artifacts throughout the original signal. Non-ideal conditions such as electromagnetic interference caused by power cables of the monitoring equipment corrupt the ECG. PLI, Baseline Wander, motion artifact (MA) and muscle artifacts (EMG) are the most common types of noise contaminating an ECG signal.