Department of Computer Science

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

Browse

Subject: search.filters.subject.Dr. Farooq Ahmad

Search Results

Now showing 1 - 9 of 9
  • No Thumbnail Available
    Item
    Formal Modeling and Analysis of Distributed Measurement Systems in Cyber-Physical Systems Using Colored Petri Nets
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Aqsa Nawaz; CIIT/FA23-RCS-002/LHR; Dr. Farooq Ahmad; LHR TP 10033
    This research addresses the reliability and consistency challenges associated with the Cyber- Physical Systems (CPS) driven Distributed Measurement Systems (DMS), which capture, collect and process DMS data or information from measurement nodes located in various geo- graphical areas. Due to being distributed and asynchronous, these systems suffer from causal inconsistencies and synchronization delays, and unstable scheduling, thereby undermining dependency in fields like power management systems and smart grids. The first stage of this approach aims to obtain a formal specification of the DMS behaviour using Computation Tree Logic (CTL) and Linear Temporal Logic (LTL). These formal languages clearly capture safety and liveness properties like the absence of deadlock, safe power switching, reliable communication, safe and correct data processing, etc. The second stage of the approach is to build a system under study, a hierarchical Coloured Petri Net (CPN) model in CPN Tools1 using well-defined ColSets, functions, transitions, guards, and inter-page communication to simulate measurement power behaviour and control switching with respect to scheduling, measurement flow, and faults. An executable and semantically rich operational model of the system is obtained from this model. The final step validates the value of the CPN model with a detailed state-space analysis. State- space properties, such as boundedness, liveness, fairness, home-state behaviour, and Strongly Connected Component (SCC), are computed and compared to formal specifications. The analysis outcomes demonstrate that the modelled system fulfils all formalisms and performs acceptably from the system operational viewpoint within the analysed state space
  • No Thumbnail Available
    Item
    Histone Explorer: AI-Enhanced Identification and Characterization of Histone Modification
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Muhammad Umar Farooq; CIIT/SP24-RCS-017/LHR; Dr. Farooq Ahmad; LHR TP 10039
    Histone modifications are one of the key epigenetic mechanisms to control the structure of chromatids and gene expression and play a pivotal role in cellular differentiation, development, and pathogenesis. In spite of the fact that Chromatin Immunoprecipitation Sequencing (ChIP-seq) is an experimental methodology that allows identifying histone marks through the use of high-resolution sequencing, it is expensive, labor-intensive and has low scalability, preventing its general use in a wide range of biological studies. To overcome these difficulties, this research suggests to consider Histone Explorer as an AI-enhanced computational system of the correct recognition and description of sites of histone modifications directly on the basis of genomic sequence information. The suggested framework will consist of a bioinformatics preprocessing pipeline that is reproducible, and sophisticated artificial intelligence models. Peaks of histone modification genomic intervals were obtained at the public repositories of epigenomic repositories such as ENCODE and Roadmap Epigenomics and mapped to a reference genome, hg38, to produce a curated FASTA sequence dataset. An extensive feature extraction scheme was used in order to obtain local and global sequence features, such as nucleotide frequency patterns, k-mer representations, positional features, pairwise interaction features, and higher-order statistical moments. It was trained and tested on the following models: CNN, BiLSTM, GRU, and attention- based transformer models among various models trained using machine learning, deep learning, and transformer-based architectures. There were 100,000 positive and negative samples of Histone sequences in the dataset. The performance of the models was strictly tested with independent test sets and using the k-fold cross-validation protocols. The experimental findings show that the transformer-based Histone Explorer model performs better than both classical and deep learning baselines with an accuracy of 91.5, precision of 90.2, recall of 92.8 and F1-score of 91.5 and AUC- ROC of 95.0. Such findings demonstrate that there is high generalization properties and strength over a wide spectrum of genomic regions. All in all, Histone Explorer offers a scalable, precise, and biologically meaningful AI-based framework of histone modifications identification. The proposed system can provide a useful computational resource in epigenetics studies, biomarker discovery, and precision-medicine studies because it lowers reliance on expensive experimental studies and allows analyzing epigenomics on a high-throughput.
  • No Thumbnail Available
    Item
    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
  • No Thumbnail Available
    Item
    Towards Automatically Resolving Biasness and Conflicts in Stakeholders Input for Requirement Prioritization
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2022) Nabiha Yaseen; SP19-RCS-026; Dr. Farooq Ahmad; LHR TP 8043
    Requirements are needed before developing any project, so these requirements are elicited from the stakeholders. Software Engineers elicit these requirements to meet the demands of the stakeholders. Software engineers find it challenging to satisfy the demands of multi stakeholders if these elicited requirements are vague or misinterpreted. To meet the accuracy, satisfaction, and expectations of multi stakeholders, prioritization of the elicited requirements is needed. Prioritizing the elicited requirements can completely prevent contract breaches or violations like budget overruns, project deadline mismatches, overshooting of delivery dates, and omitting crucial requirements during development. There are various techniques have been introduced in this area, but the problems related to RE are still under research in terms of lack of collaboration among multi stakeholders, Developer’s effort in eliciting conflicted requirements and to make changes after, and resource and time waste. To address these problems, we designed an approach called the Collaborative Requirements Elicitation Tool (CRET), which is intended to facilitate and improve efficient collaboration between multiple users to get the best from requirements elicitation. To enable multiple stakeholders to cooperatively elicit the same goals and requirements toward project that are conflict-free and unbiased, our tool has been designed and developed in a way to support the real-time communication and collaboration among them and to get the requirements on which they are collaboratively satisfied. Our proposed tool was evaluated for its ability to get best accuracy measures to eliciting the requirements in an unbiased, conflict-free, collaborative, timely efficient and lowering the developer’s effort manner. In our proposed tool CRET, requirement elicitation was done collaboratively, by using the Point P rating technique to set the requirement prioritizing values and employed the k-mean clustering algorithm prioritize the elicited requirements. Introduced two new features in this research is the report requirement feature and other is authority approval to remove the conflicts before forwarding the requirements for prioritization. We utilized the PHP LARAVEL framework to develop this web-based tool. With groups 2 of requirement engineers and client stakeholders, we conducted a user study to evaluate the tool, focusing on requirement elicitation and prioritization using CRET. The study's findings indicate that our proposed automated tool support can assist multiple stakeholders in collaborative communicating with other stakeholders more effectively to produce better and improved requirement elicitation, and our tool eliminates conflicts and biases of multiple stakeholders during elicitation through their collaboration. Our tool works in the four operational steps collaboratively RE (requirement elicitation), RRR (Req rating and reviewing), AA (authority approval) and RP (requirement prioritizing). In the RE phase of the software development life cycle; RP is a task that relates to multi phase decision making. It is mostly used for software release planning and influences the creation of the best software product by eliciting stakeholders' preferred needs.
  • No Thumbnail Available
    Item
    Automatic Code Generation of Petri Net-Based Business Process Models
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2021) Rana Marwat Hussain; SP19-RCS-021; LHR TP 7292; Dr. Farooq Ahmad
    To verify software system flows and different components before the implementation of the system formal modeling techniques become very useful. Modeling helps users to understand software systems better by defining the system’s components formally. Many mathematical modeling languages are used for this purpose but the widely used language for formal modeling is Petri Nets. Traditionally all the efforts involved in the modeling phase is nothing more than to support the documentation because the development process manual transfer the modeling into implementation which because information lost is the real system implementation (program Code Generation). To reduce the implementation and modeling gap Model-Driven Software Engineering (MDSE) plays a very crucial role as MDSE approaches favor code generation from models which helps to improve productivity, quality of the application and reduce the time spent on implementation. As code generation is the fundamental part of the MDSE and model play a key role that is why tool support proposed in this thesis work tool provides a modeling interface and an approach to generate code from Petri net in multiple high-level programming languages such as Python, C, C++, Java, etc. Through the use of modeling interface, four models have created these models were used to generate code and the tool successfully generated code in multiple high-level programming languages which can be compiled and run-on supportive IDEs. However, the proposed tool had flaws in the modeling such as the CTRL+ key sometimes misses the draw arc operation, and code generated from complex models has logical flaws. The proposed tool can be useful in future research work for providing support to extend the code generation approach, and modeling interface to modeled other domain’s model which based on another formal modeling also to support the other informal modeling languages such as UML class diagram, etc. and help to generate code
  • No Thumbnail Available
    Item
    Petri Net Based Formal Semantic Extraction from Code
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2021) Shafaq Naz; SP19-RCS-017; LHR TP 7293; Dr. Farooq Ahmad
    Due to the rise of reverse engineering practices from the last two decades, worth of design engineers become highlighted. Therefore, the point of concern is the verifiability of the reverse engineered architecture, because these practices are more likely to use in safety critical systems. Hence, a prototype is needed to verify or to validate the reverse engineered design or module of the legacy system to use in further applications to evade future loss. Therefore, dynamic analysis of the system is main concern which is not possible through direct reversing from the source code. It may include multiple execution trace analysis of the system. Generating a diagram, representing the design of the application, from the code helps to study the runtime behavior of the application. However, diagrams are an informal representation of the behavior which do not support verification and validation of the application. Therefore, there is a need to generate the formal representation of the application. This research focus on the automatic generation of Petri net models from code which describe the behavior of the application as well as its verification. Moreover, generating Petri net formal model from code is a challenging task which is the focus of this research. Firstly, a systematic literature review and comparison of different reverse engineering tools will be performed to critically find out the research gap. Further, this research will proceed to provide a framework to reverse engineer the formal representation of code to understand the behavior the system
  • No Thumbnail Available
    Item
    Formal Modeling and Analysis of Security Schemes in Internet of Things
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2020) Muhammad Amar Sohail; FA16-RCS-020; LHR TP 5971; Dr. Farooq Ahmad
    The Internet of Things (IoT) has provided us with the notion of a smartly connected world. Internet of Things is a system in which gadgets, computing machines or mechanical devices, are connected with each other through Unique IDs. Those objects can accumulate and disseminate the packets from one node to other nodes without any human participation. As IoT is related to the network-based distributed systems such as i.e. Cloud Computing, Fog Computing, and Body Area Network etc. These networks when applied to sensitive and confidential infrastructure then the role of its security becomes very crucial. To this end, routing strategy is responsible and literature suggests different techniques for security and privacy in IoT Systems. Formal modeling of a system can help us to check the reliability, accuracy and consistency of the system. Colored Petri Nets is graphic-based language and it has taken premium space in design and specification, validation and verification of systems which are concurrent in its behavior. Security Scheme is the mechanism of securing a network system by setting up routing strategy through topology. Analysing the attacks and mitigating them is a small subset of security schemes. In this study Routing over Low Power and Lossy networks (RPL) is used as a case study and the aim was to present the idea of translation of into formal language and ultimately analyze its security with the means of Formal Specification Methods. RPL is an IPv6 protocol and prominent for the routing in Internet of Things. Eventually, the focus will be shifted towards the evaluation of the existing security standards for RPL through formal validation and verification to check if those standards can achieve the desired security level.
  • No Thumbnail Available
    Item
    Computer Vision Based Pattern Matching and Displacement Detection During Fabric Printing
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2017) Muhammad Abdul Qayum; FA10-PCS-001; LHR TP 5799; Dr. Farooq Ahmad
    There is an absolute need for the robust quality inspection system, which can take on the new challenges and overcome the human limitations to inspect the fabric production consistently. To address this gap, computer vision based techniques are employed by enterprises. Some of the beneficent manufacturers include ceramic, circuit board printer, paper printer and textiles. Excellent work has been done in the yarn and weaving production sections of textile industry, however fabric printing monitoring is being explored by the researchers. The referential approach is mostly adopted to monitor fabric printing for defect detection. It works by acquiring an error-free image and registering this image with subsequent images captured during the production. In this method, the major time-consuming problem is to find the design repeat in the sample image before further processing. The researchers suggested some methods like distance matching in RGB space, photo encoders, genetic algorithm along with recursive splitting, Fuzzy C-means clustering, and cross correlation algorithm. There are certain limitations with these methods, for instance, sensitive to small deformation, required extra hardware prone to mechanical fault and it is expensive in calculations. In this research, a method for finding the design repeat is proposed. The method is tuned up according to the textile printing domain. Since the fabric moves in one direction during printing process, therefore the image registration can be confined to the same direction. To further speed up the process, the image registration method is applied using few initial pixel columns of the reference image with the sample image. Such bunch of selected columns of the reference image is matched with the same number of columns selected from sample image by moving this bunch on the sample image column by column. The maximum matching position is marked as the start of the design repeat. As the repeat size is always fixed, therefore complete design can be extracted from acquired image for defect detection. The experimental results on different fabric designs using the above-mentioned method are promising. Moreover, xi this technique improves the image alignment speed which enhances defect detection system performance. The most common defect is the displacement or misregistration of a colour. This defect is caused by the misalignment of cylindrical screens of fabric printing machine. As every screen is responsible for a colour, the misaligned screen registers the colour on the incorrect position. It leads to defective production and contributes to a substantial loss of the material and time. Few researchers proposed the feature based solution which are either computationally expensive or do not provide detail information about the defect like location and colour. Further, some techniques depend on the additional algorithms to find defects. Mostly, these methods depend on the accuracy of reference and sample image alignment. So there is always a chance of wrong notification. An improved algorithm for the detection of displacement of a colour during fabric printing is proposed in this thesis. The algorithm concatenates red, green and blue pixel values of the RGB image to represent a colour and later produces a frequency distribution of different colours for both sample and reference images. The colours with low frequencies are removed considering noise. In the next step, colours are grouped depending upon their distances from each other. These colour groups are later used to detect any new colour in the sample image which is actually created by the displacement defect and colour variation. The proposed algorithm successfully detects displacement and colour variation defects when it is tested using different flawed printed fabric images. The result shows that the proposed method has almost same accuracy as stat of the art algorithm and more helpful to detect the colour displacement, and it can also overcome the shortcoming of repeat finding process.
  • No Thumbnail Available
    Item
    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.