Final Year Projects (FYPs) - Undergraduates

Permanent URI for this collectionhttps://repository.cuilahore.edu.pk/handle/123456789/64

This collection archives the complete set of theses produced by students of the COMSATS University Islamabad, Lahore Campus.

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    INTERNSHIP AT AUR-LAB
    (Library Information Services COMSATS University Islamabad Lahore Campus, 2024-04-02) FAZEEL UMAR; FA20-BST-002; Dr. Mian Muhammad Farooq
    AUR Lab is a cooperative venture between Predominant College, as of now positioned No. 1 private for influence among private colleges in Pakistan (QS Positioning), and We-Plan, an Australian plan firm working in Pakistan. In the span of 10 months of foundation, it has accomplished the achievement of one of its startup projects being shortlisted among top two out of roughly 100+ entries from Pakistan in the Endeavor Cup Global contest. Current undertakings are managing in various business ventures, including archeological the travel industry; Metaverse; NFT Commercial center; administration and casting a ballot; Style plan; healthcare; Shrewd Agrarian; environmental the travel industry; structural plan; AR-based promoting; energy effectiveness; street wellbeing; orientation equity; also, land income. Our group of specialists incorporates specialized staff as well as business improvement staff: Dr. Muhammad Ashraf Khan; Prof. Saleem Zubair; Ms. Qurratulain Sonia Kashmiri; Mr. Muhmmad Ahmad; Mr. Jawad Ahmad; also, Mr. Javaid Iqbal
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    INTERNSHIP REPORT AUR LAB
    (Library Information Services COMSATS University Islamabad Lahore Campus, 2024-04-02) Nouman Ali; Dr. Mian Muhammad Farooq
    LAB is a collaboration between Superior University, which is presently ranked first in Pakistan for effect among private universities (QS Ranking), and we Plan, an Australian design business based in Pakistan. Within 10 months of its inception, one of its startup initiatives was selected as one of the top two out of about 100+ proposals from Pakistan in the Venture Cup International competition. Current projects include archaeological tourism, Metaverse, NFT Marketplace, governance and voting, fashion design, healthcare, Smart Agriculture, ecological tourism, architectural design, AR-based advertising, energy efficiency, road safety, gender equality, and land revenue. Dr. Muhammad Ashraf Khan, Prof. Saleem Zubair, Ms. Qurratulain Sonia Kashmiri, Mr. Muhmmad Ahmad, Mr. Jawad Ahmad, and Mr. Javaid Iqbal are among our technical and business development professionals.
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    CRESCENT BAHUMAN LIMITED
    (Library Information Services COMSATS University Islamabad Lahore Campus, 2024-04-02) Maydah Azhar; FA20-BST-008; Dr. Riffat Jabeen
    Bahaman Limited. The purpose of this report is to demonstrate the practical application of my academic knowledge and skills in a real-world business setting. With more than 60 years of experience in industries as diverse as textiles, sugar, banking, insurance, food, agriculture and steel, Crescent Group has built a solid reputation in Pakistan's business community. Crescent Bahaman was initially formed as a joint venture between Crescent Group and Greenwood Mills. It has been wholly owned by the Crescent Group since 2001. In FY21, the Pakistan's commodities expanded by 14% insufferable from a low-base impact, coming about because of the pandemic prompted lockdown in 2020. By and large, the figures of commodities stay inside the scope of USD 22-25b, which is in accordance with the pattern of past ten years. The portion of materials in complete products has generally been 54-59%; coming in at 57% during FY21. The low-base impact was articulated in material area also, with the post-lockdown increase of around 13% in the products. Pakistan's material commodities have CAGR of 4.4% during long term period from FY19 to FY21. Inside the materials, high worth added fragment held the most extreme offer, which has been moving vertically or most recent three years, expanding from 73.9% in FY19 to 80.7% in FY21. Knitwear, readymade pieces of clothing, and bed wear comprise the significant part of this portion.
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    INTERNSHIP ON AUR-LAB
    (Library Information Services COMSATS University Islamabad Lahore Campus, 2024-04-02) Muhammad Samran; FA20-BST-003; Dr. Muhammad Noor-ul-Amin
    AUR-LAB is a collaboration between Superior University, which is presently ranked first in Pakistan for effect among private universities (QS Ranking), and we Plan, an Australian design business based in Pakistan. Within 10 months of its inception, one of its startup initiatives was selected as one of the top two out of about 100+ proposals from Pakistan in the Venture Cup International competition. Current projects include archaeological tourism, Metaverse, NFT Marketplace, governance and voting, fashion design, healthcare, Smart Agriculture, ecological tourism, architectural design, AR-based advertising, energy efficiency, road safety, gender equality, and land revenue. Dr. Muhammad Ashraf Khan, Prof. Saleem Zubair, Ms. Qurratulain Sonia Kashmiri, Mr. Muhmmad Ahmad, Mr. Jawad Ahmad, and Mr. Javaid Iqbal are among our technical and business development professionals.
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    INTERNSHIP REPORT ON BAIG ELECTRICAL COMPANY (PVT.) LIMITED
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Fakhra Manzoor; CIIT/FA21-BST-009/LHR; Dr. Riffat Jabeen; LHR TP 9957
    When I was working as an intern in Baig Electrical Company (Pvt.) Ltd., I was blessed to work with an organization that was electrical based and I was able to develop on several of these skills. The type of tasks included data entry and auditing; in this way, I gained knowledge of the finance department. The management practices that were explained to me were useful in realizing that people have various responsibilities within a firm. I have appreciated various aspects of how a business runs and the many roles I can take on depending on the sector. In the course of my internment, I engaged myself with multiple exercises that were entirely a new and unique experience to me. They allowed me to participate in testing processes, which provided me with practical experience that I needed. I also came to appreciate quality assurance and got to deal with transformers and switch gears, which I found out are among the company’s biggest brands in the market. This exposure has given me this information on the competition in the electrical sector. I understood the importance of product quality and safety standards in situation to the electrical field which are the critical factor of electrical products and systems’ reliability and safety. It equipped me with technical know-how in and out, soft skills as a team player, good communicator and critical thinker.
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    Spatial and Temporal Analysis of Drought
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2023) Muhammad Furqan Ahmad; CIIT/FA19-BST-002/LHR; Dr. Mian Muhammad Farooq; LHR TP 9937
    In the recent years climate change is the hot topic of research. Climate change can have severe effect on the environment. The drought is an important factor of the climate. If a drought occur in some area it will affect the agriculture, water resources and other important factors of the country. In this study, the impact of drought in different districts of Punjab, Pakistan was studied using Standardized Precipitation Index (SPI) and Standardized Anomaly Index (SAI). The SPI is applied on the rain data and the SAI was applied on the temperature data. The data was collected from Pakistan Metrological Department. At first, we fit the data on Length Biased Exponential Distribution and then we applied Standardized Precipitation Index on the rain data received from Pakistan Meteorological Department from 1993 to 2022. We also computed SPI using 3-month, 6-month, and 12-month moving average of the original data. We conducted spatial and temporal analysis using SPI and for the visual representation we also plot maps of the past five years for better understanding of the drought. Standardized Anomaly Index (SAI) is a useful tool to measure and monitor deviations from normal conditions in terms of temperature or other relevant variables associated with drought. We used temperature to better explain the drought impact in Pakistan. After applying SAI, we find out that temperate of the data is above average which means there is drought impact in different districts of Pakistan. The results show the clear drought pattern in different districts of Pakistan. We ignore the 0 and negative values of rain data before fitting the Length Biased Exponential Distribution as it is undefined for these values and then we compute the results. The graphs show that after taking moving average the drought patterns decrease in districts and also few years does not show any drought pattern.
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    INTERNSHIP REPORT OF BUREAU OF STATISTICS, GOVERNMENT OF PUNJAB, LAHORE
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Shafaq Ikram; CIIT/FA21-BST-021/LHR; LHR TP 9933
    The Bureau of Statistics (BOS) of the Government of Punjab plays a pivotal role in the collection, processing, and dissemination of statistical data within the province. Operating under the Department of Planning and Development, BOS is responsible for ensuring that statistical activities are conducted in accordance with the standards set by the National Statistical Council. Its primary functions include the collection of provisional data in standardized formats, coordination of statistical activities both within the province and in relation to the federal statistical system, and the provision of comprehensive statistics through collaboration with various cognate institutions. Additionally, BOS is tasked with conducting new censuses and surveys to enhance the availability of reliable data. This extensive infrastructure enables BOS to effectively gather and disseminate statistical information that is crucial for informed decision-making and policy formulation. Pakistan's statistical system has its roots in a decentralized framework established at the time of independence in 1947. Initially, statistical activities were primarily viewed as a utility for administrative functions. The Central Statistical Office (CSO) was established in 1950 as an Attached Department within the Economic Affairs Division, taske
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    BUREAU OF STATISTICS, PUNJAB
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) FIZA SALEEM; CIIT/FA21-BST-010/LHR; LHR TP 9931
    The Bureau of Statistics, Punjab, operates as the principal agency for statistical data management within the province. Functioning under the Planning and Development Department, BOS Punjab is tasked with the comprehensive collection, processing, and dissemination of statistical information. This data is disseminated through periodic publications and digital platforms, ensuring accessibility and transparency. BOS Punjab’s mandate, as defined by the National Statistical Council, encompasses the collection of provincial-level data, coordination, and support of statistical activities across Punjab, and liaison with the Federal Statistical system. The organization is also responsible for preparing and diffusing provincial indicators by collecting data from various institutional sources and conducting new censuses and surveys. The Bureau’s Head Office is situated in Lahore, supported by a network of 9 divisional and 7 district field offices across the province, ensuring extensive reach and data coverage.
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    A study of ordered random variables for Reflected Power Function Distribution
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Maydah Azhar; CIIT/FA20-BST-008/LHR; Dr. Riffat Jabeen; LHR TP 9953
    This thesis presents a comprehensive study of ordered random variables for the Reflected Power Function Distribution (RPFD). The primary focus is on the statistical properties, parameter estimation methods, and applications of the RPFD. The RPFD is a transformation of the traditional Power Function Distribution, which is frequently used to model phenomena in various fields such as hydrology, economics, and engineering. By reflecting the distribution around its midpoint, the RPFD provides a mirrored perspective that is particularly useful for scenarios where probabilities are skewed in the opposite direction. The study begins with an introduction to the Power Function Distribution and its reflection to form the RPFD. The properties of the RPFD, including its probability density function, survival function, hazard rate function, and moments, are thoroughly explored. Various parameter estimation techniques such as Maximum Likelihood Method (MLM), Modified Maximum Likelihood Method (MMLM), and percentile-based estimators are discussed in detail. Furthermore, the thesis delves into generalized order statistics (GOS) and their specific application to the RPFD. This includes the derivation of the probability density function (PDF) and joint PDF for GOS, as well as the calculation of mean, variance, and covariance for different scenarios. The literature review highlights key studies and methodologies that have contributed to the development and understanding of order statistics and RPFD. Empirical analysis using real-life data sets demonstrates the practical utility and superior performance of the RPFD compared to other models. Overall, this research contributes to the statistical theory by providing new insights and tools for the application of the RPFD in various scientific and engineering disciplines.
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    Modified Radial Basis Function Network (RBFN) by Bayesian Regression for predicting Synthetic Cancer
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Fazeel Umar; CIIT/FA20-BST-002/LHR; Dr. Mian Muhammad Farooq; LHR TP 9948
    This thesis investigates the use of Long Short-Term Memory (LSTM) networks to predict Google’s stock prices. The study focuses on stock data from January 2012 to December 2016 for training, and January 2017 for testing. LSTM, a type of Recurrent Neural Network (RNN), is ideal for time series forecasting because it can learn long-term dependencies. To prepare the data, stock prices were normalized using Min Max Scaler, which helps improve model performance. The data was then organized into sequences of 60-time steps using a sliding window approach. The LSTM model was built with four layers, each containing 50 units, and included dropout layers to reduce overfitting. Training was conducted using the Adam optimizer and mean squared error as the loss function over 100 epochs with a batch size of 32. The results showed that the LSTMmodel effectively captured the stock price patterns, highlighting its potential for accurate financial forecasting.
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