MS: Recent submissions

  • A Framework for Healthcare Management System Using Predictive Analysis of Diseases 
    Nakhat, Khulood (College of Electrical & Mechanical Engineering (CEME), NUST, 2020)
    Disease outbreak detection is a major challenge in public health informatics. While big data in healthcare is constantly expanding, there still exists a need to effectively integrate and represent data in order to obtain ...
  • Deep learning-based analysis and classification of COVID patient through CT images 
    Alam, Maria (College of Electrical & Mechanical Engineering (CEME), NUST, 2021)
    The world is facing a prodigious pandemic initiated through SARS-CoV-2. Corona Infection was first emerged and recognized in Wuhan China which became a global pandemic. Industries all around the world are crippled and many ...
  • DSP SPECIFIC OPTIMIZED IMPLEMENTATION OF VITERBI 
    Asfia, Yame (College of Electrical & Mechanical Engineering (CEME), NUST, 2009)
    Due to the rapid changing and flexibility of Wireless Communication protocols, there is a desire to move from hardware to software/firmware implementation in DSPs. High data rate requirements suggest highly optimized ...
  • PEROMANCE ANALYSIS OF OFDM SYSTEM CONSIDERING QUANTIZATION EFFECTS 
    Pervez, Imran (College of Electrical & Mechanical Engineering (CEME), NUST, 2009)
    This thesis presents the effects of fixed point implementation on the performance of a digital communication system. In recent times orthogonal frequency division multiplexing (OFDM) has emerged as a promising technology ...
  • TH-SOF-1923-CXR Image-Based Classification of COVID-19 using CNN Model 
    Fareed, Wajeha (College of Electrical & Mechanical Engineering (CEME), NUST, 2021)
    Novel COVID-19 has dispersed all over the world and had taken many lives. Many of them are still fighting against this infectious virus. This virus has not only exaggerated the health of people but has also let down ...
  • Trend Analysis of Terrorist Incidents in Pakistan-1996-2017 
    khan, Imran (College of Electrical & Mechanical Engineering (CEME), NUST, 2021)
    Pakistan is one of the highly effected countries of the world from terrorism, this project is consisting of three different parts which are Trend Analysis, Terrorist Groups Classification and Incident Date Prediction. ...
  • Utilization of DCT Coefficients for the Classification of CIFAR-10 & CIFAR-100 Datasets 
    Chaudhary, Laiba Naeem (College of Electrical & Mechanical Engineering (CEME), NUST, 2020)
    In this work we propose efficient deep neural networks for classification that are well suited to the edge computing and cloud computing environment. These environments inherently have to deal with bandwidth limitations ...
  • Service Chaining in Network Function Virtualization 
    Tariq, Muhammad Arslan (College of Electrical & Mechanical Engineering (CEME), NUST, 2020)
    Network function virtualization (NFV) is a network built by an architectural concept and technique that involves the different information technologies for the virtualized functioning of different nodes and switches ...
  • A Framework for Healthcare Management System Using Predictive Analysis of Diseases 
    Nakhat, Khulood (College of Electrical & Mechanical Engineering (CEME), NUST, 2020)
    Disease outbreak detection is a major challenge in public health informatics. While big data in healthcare is constantly expanding, there still exists a need to effectively integrate and represent data in order to obtain ...
  • Recognition of Different Disastrous Events Using Convolutional Neural Network 
    Shafique, Dania (College of Electrical & Mechanical Engineering (CEME), NUST, 2020)
    Natural disasters or crises include earthquakes, land sliding, floods, and typhoons causing great damage to manmade structures such as buildings. To efficiently manage natural disasters, it is important to develop an ...
  • Human Activity Recognition Using OpenPose and Neural Network 
    Khan, Hesham Mahmood (College of Electrical & Mechanical Engineering (CEME), NUST, 2021)
    Human Activity recognition are the most implemented area of Machine learning and Neural Networks. Previous studies in this area show how Human activity recognition system perform on images of where poses of a person need ...
  • Segmentation and Classification of Phonocardiogram Signals using Machine Learning Techniques 
    Afshan, Zo- (College of Electrical & Mechanical Engineering (CEME), NUST, 2020)
    Cardiovascular diseases (CVDs) are one of the major causes of deaths in the world. CVDs generally describe the conditions of the heart that involve narrowed or blocked blood vessels, causing heart attack, angina or stroke. ...
  • Automatic Prognosis System Using Recurrent Neural Network for Prediction of Alzheimer Disease 
    Aqeel, Anza (College of Electrical & Mechanical Engineering (CEME), NUST, 2021)
    Alzheimer’s disease (AD) is a type of brain malfunction mainly found in old-aged people; it is irreversible and develops over time. Usually, people with AD experience initial memory loss, ultimately leading to their ...
  • Memory Optimization of CNN for Reconfigurable Architectures 
    Iqbal, Muhammad Jawad (College of Electrical & Mechanical Engineering (CEME), NUST, 2021)
    Deep neural networks have become the most advanced method for solving computer vision problems. Although they are much Powerful, big amount of weights requires significant storage space. So, these deep Neural networks ...
  • Framework for Cognitive Stress Detection Using ECG and GSR Signals 
    Umbreen, Ayesha (College of Electrical & Mechanical Engineering (CEME), NUST, 2022)
    In today's culture, mental illnesses like stress have just recently become social problems. Stress is the term used to describe the bodily and mental reactions to physical, emotional, or mental factors. A person's mental ...
  • sEMG Signal Analysis using Hand Crafted Features for Detection and Classification of GTC Seizures 
    Naveed, Maryam (College of Electrical & Mechanical Engineering (CEME), NUST, 2022)
    Seizures with a greater possibility of sudden unexpected death in epilepsy (SUDEP) deteriorates the efficiency of life. Significantly, it is of prime importance to lessen all the factors that are involved in worsening ...
  • Analysis of EEG signals using deep learning to highlight effects of vibration-based therapy on brain 
    Safder, Syeda Noor-Ul-Huda (College of Electrical & Mechanical Engineering (CEME), NUST, 2022)
    Rehabilitation of patients with neurological disorders is a life-long process accomplished through pharmacological and non-pharmacological procedures for patient management. One non-pharmacological treatment that has ...
  • Block-chain Enabled Transaction Integrity for Industrial IOT 
    Syrum, Khan (College of Electrical & Mechanical Engineering (CEME), NUST, 2022)
    The rapid advancement of IOT has caused a lot of device to get connected to the IOT. This has caused a humongous increase in IoT data. IOT users are facing issues with the security of their data and centralization; these ...
  • Brain Tumor Segmentation of MRI Images Using Gabor Filter with Deep Learning Architectures 
    Sultan, Muhammad Ubair Bin (College of Electrical & Mechanical Engineering (CEME), NUST, 2022)
    Perfect segmentation of different region and subregions of gliomas from MRI scans has extremely high impact on treatment and diagnosis of brain tumors. .However, segmentation of the subregions is a difficult task because ...
  • A Lecture-Slide Centric Automated Distractor Generation for Post-Graduate Software Engineering Courses 
    Chughtai, Rudeema (College of Electrical & Mechanical Engineering (CEME), NUST, 2022)
    Critical circumstances, natural disasters or pandemics like COVID 19 gave rise to the wide applicability of E-learning into education system. To utilize the inevitable benefits proposed by E-learning, an efficient and ...

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