MSCS: Recent submissions

  • GPT Transformer Based Story Points Effort Estimation in Agile Software Development 
    Cheema, Amna Shahid (MCS, 2023-08-07)
    The process of accurately estimating the effort required to complete user stories is a crucial activity in software development. It has the potential to significantly impact both the predictability and efficiency of the ...
  • Cost Estimation Through Story Points in Agile Software Development Using Machine Learning Techniques 
    Javed, Aimen (MCS, 2023-08-02)
    Software development is growing rapidly in the up-to-the-minute era. The development process involves estimating the effort, which is segmented into cost and time, to have a clear direction for the development progression. ...
  • Detection of DDOS Attacks in A Smart Building Using ML 
    Yumna Nasir, Supervised by Assistant Professor Dr Yawar Abbas Bangash (MCS, 2023-08-21)
    Smart buildings, enabled by the widespread use of Internet of Things (IoT) devices, are becoming increasingly prevalent. However, this rise in IoT adoption also brings new security challenges, with smart buildings more ...
  • Improving Text-To-Image Generation with Multimodal Semantic Coherence In Adversarial Training 
    Rahat Afza, Supervised by Prof. Dr. Hammad Afzal (MCS, 2023-08-15)
    Research in the field of text to image generation has shown incredible momen- tum owing to the availability of more powerful natural language processing (NLP) models and generative networks. The quality of data representation ...
  • Cardiovascular Disease Recognition Using Multiple Machine Learning Algorithms with Feature Scaling Technique 
    Arslan Naseer, Supervised by Assoc Prof Dr. Fahim Arif (MCS, 2023-07-31)
    Cardiovascular disease (CVD) believes to be a major cause of transience and indisposition worldwide. Early diagnosis and timely intervention are critical in preventing the progression of CVD and improving patient outcomes. ...
  • Guidelines for Making Web Accessible of Dyslexics 
    Rao, Hamna; Supervised by Dr. Tauseef Ahmed Rana (MCS (NUST), 2022-08)
    Dyslexia is a specific learning disorder that affects the reading, writing, spelling and decoding abilities. The people suffering from dyslexia, experience difficulties while using websites because designers, developers ...
  • Transformer Based Sequential Recommender System 
    Farooq, Nadia; Supervised by Dr. Naima Iltaf (MCS, 2023-01)
    Recommender systems (RS) aids in helping endusers by providing suggestions and predicting items of their interest in e-commerce and social media platforms. Sequence of user’s historical preferences are used by Sequential ...
  • Adaptive Trust Calculation in Fog Computing 
    Nawaz, Alishba; Supervised by Dr. Main Muhammad Waseem Iqbal (MCS, 2023-04)
    Fog is well suited for situations where a huge number of decentralized devices must communicate, provide live analysis of data, and perform storage jobs because of its inherent decentralized nature and capacity to process ...
  • Low Resource Language Named Entity Recognition for Social Media Text 
    Issa, Aamir; Supervised by Dr. Shibli Nisar. (MCS, 2023-04)
    Named Entity Recognition (NER) is the part of Natural language processing (NLP) that helps to identify and classify the name entities such as people, location and organization names. Named Entity Recognition also played a ...
  • Replication of Multi-Agent Reinforcement Learning for “Hide & Seek” Problem 
    Kamal, Muhammad Haider; Supervised by Dr. Muaz Ahmed Khan Niazi (MCS, 2023-04)
    Reinforcement learning generates policies based on reward functions and hyperparameters. Slight changes in these can significantly affect results. The lack of documentation and reproducibility in Reinforcement learning ...
  • An Efficient Deep Learning-Based Classification Framework for Hypertensive Retinopathy 
    Sajid, Muhammad Zaheer; Supervised by Dr. Nauman Ali Khan (MCS, 2023-04)
    Hypertensive retinopathy (HR) is a well-known eye disease that is caused by high blood pressure (hypertension). In this illness, symptoms typically develop later. The AV nicking, cotton wool patches, constricted veins in ...
  • Selecting Software Architectural Styles from Requirement Documents Using NLP 
    Javeria Yasmin; Supervised by Dr. Yawar Abbas Bangash (MCS, 2023-02)
    With the growth in the size and complexity of softwares, the design phase of software systems has recently drawn more attention. Software architecture is a fundamental idea in this phase and has a significant impact on the ...
  • Selecting Software Development Life Cycle (SDLC) Models from Requirement Documents Using NLP 
    Gul, Mahria; Supervised by Dr. Yawar Abbas Bangash (MCS, 2023-02)
    The success of software system depends on many factors among which the selection of most suitable Software development life cycle (SDLC) model is the most significant. SDLC represents a framework to develop a software ...
  • Analysis and Selection of Optimized Machine Learning Techniques for Software Bug Prediction 
    Ain, Noor ul; Supervised by Dr. Fahim Arif. (MCS, 2023-01)
    Software Bug Prediction is an active research area and is being widely explored with the help of Machine Learning. Since bug prediction is now considered as an important measure of SDLC, we need to have optimized techniques ...
  • Using Vision Transformers (ViT) For Low-Level Vision Enhancement 
    Daud, Muneeba; Supervised by Dr. Hammad Afzal. (MCS, 2023-01)
    Restoring and enhancing underwater images is a significant issue in image processing and computer vision. Poor underwater imaging quality is caused by the scattering and absorption of light by underwater contaminants. ...
  • Performance Analysis of IDS Using Feature Selection and ML Methods 
    Khan, Muhammad Muheet; Supervised by Dr. Fahim Arif. (MCS, 2022-12)
    Intrusion detection system (IDS) in past many years has played an important part in improving performance of systems by avoiding and preventing false attacks on the systems to make the networks more safe and secure. Now ...
  • Speech Corpus Generation For Low Resource Language (Pashto) 
    Shoaib, Muhammad; Supervised by Dr. Shibli Nisar. (MCS, 2022-12)
    Meta AI’s new unsupervised speech recognition framework (wav2vec variants) is the latest development of several years of work in speech recognition models, data sets, and training techniques. The wav2vec model has changed ...
  • Demographical Based Sentiment Analysis for Detection of Hate Speech Tweets 
    Safdar, Kamal; Supervised by Dr. Shibli Nisar. (MCS, 2022-12)
    As online content continues to grow, so does the spread of hate speech. The use of vast online social communication forums helps the user to express their opinion freely at any time. While the ability to freely express ...
  • Visual Programming Languages a Comparative Analysis of VPL 
    Pervez, Laiba; Supervised by Dr. Fahim Arif. (MCS, 2022-12)
    The task of selecting which VPL is ideal for learns are a problem foe college students and professor alike. They had been unable to concentrate on good judgment and tried to observe grammar rather, which was a terrible ...
  • Automatic Detection of Offensive Language for Roman Punjabi 
    Kahoot, Muhammad Zeeshan; Supervised by Dr. Shibli Nisar. (MCS, 2022-11)
    Cyberbullying has emerged as a deadly nuisance for social norms and ethics, posing one of the most critical challenges for researchers to detect and monitor cyberbullying on social media platforms through the use of offensive ...

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