Department of Computer Science

Permanent URI for this communityhttps://repository.cuilahore.edu.pk/handle/123456789/16

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Author: search.filters.author.Dr. Farooq AhmadSubject: search.filters.subject.Applied mathematics

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    Data Driven Prediction of Student Performance: Integrating Academic, Social, Personal and Behavioral Factors in Pakistan Higher Education
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Frazeen Babar; FA22-RCS-026; LHR TP 9490; Dr. Farooq Ahmad
    Student performance is an important aspect of any educational institution. Several factors affect a student’s performance, e.g., learning assessments, co-curricular activities, previous achievements, personal and social Interactions, etc. Currently, in Pakistan, there is a lack of any such system that helps to analyze and predict student performance. There are two primary reasons for this, 1) lack of research into existing prediction methods to determine the best suitable approach for evaluating student performance in Pakistani institutions, 2) limited research on the factors that influence specifically Pakistani students' performance. The essential goal of this research is to foster predictive models for GPA evaluation using machine learning (ML) and deep learning (DL) techniques. The main research problems explore the efficiency of various features and algorithms in predicting students' cumulative GPAs (CGPA) and pass/fail outcomes. To close this gap, we first gather a sizable dataset of several characteristics that influence a student's academic success in this study project. The COMSATS University, Lahore Campus students studying computer science and software engineering are the source of the data. Additionally, we assessed the suggested dataset using (ML & DL) models to forecast students' performance in terms of regression (CGPA) and classification (pass/fail). The assessment is conducted utilizing f-score, accuracy, precision, and recall. The examination of RMSE, R2 , and MAE is used to assess the performance of regression techniques. The results of this study might be advantageous to academic institutions, teachers, and students. The study concludes by promoting the use of predictive models to backing academic interferences and institutional planning, with the potential for wider approval in several educational situations
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    Colored Petri Net Based Modeling And Analysis
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2018) Usman Younas; FA16-RCS-027; Dr. Farooq Ahmad; LHR TP 5621
    Efficient and safe transportation systems are essential part of modern society and developed cities. Logistics and communications play a vital role in the economy of any country. Rail transport systems are considered as backbone for freight and passenger movement across long distances. Developing a secure rail transportation system for a developing country like Pakistan is a challenging task due to weak infrastructure and less public awareness. A secure transport system can reduce chances of collision and result in saving human lives and economy. Formal modeling of a framework or a system can assist us with checking unwavering quality, precision and consistency of the framework or system. It helps us to check the validity and authenticity of the system before the actual product comes in hand. System can be viewed from different aspects through formal specification for better understanding. Modifications in the model at design level is also possible if there are any flaws in our formal model. Railway transportation systems are safety, monetary and environmentally critical systems since its failure may cause serious outcomes, for example, loss of human life, extreme wounds, and huge size of natural harms or extensive financial disasters. Rail transport is a distributed system consist of many concurrent process occurring in parallel fashion. So the safety and heterogeneous nature of this framework requires formal modeling for its development and advancement. The fundamental focus of this study is to build up a moving block railway operation system with dispatching segments to keep away trains from crashes and wrecking. Formal modeling and analysis of the operation system will also be performed to check the consistency and reliability. A core technique for the proposed research work would be the colored Petri nets (CPNs) based on discrete and concurrent system modeling, which will be used for simulation and verification of the operation model of system. CPN is the third class of Petri nets and it is a combination of Petri Nets and Standard Meta Language (SML). After model simulation, a series of analysis checks will make sure the authenticity and consistency of the model.