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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The Impact of Socioeconomic Factors and Parental Involvement on Functional Challenges of Children
(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-02-01) Muhammad Samran; CIIT/FA20-BST-003/LHR; Dr. Muhammad Noor ul Amin; LHR TP 9949
Functional difficulties that children experiencing today is including a range of cognitive and emotional,; social and behavioral problems greatly affect there academic performance as well as their ability to form appropriate relation and adjust overall. The problems regularly continue into adulthood with consequences on multiple areas of life. By the; understanding the more various factors of irresponsibility is very much important for successful joining and assistance. Having this complexity or challenge the purpose of the study was to illuminate how parental participation and socio-economic status are linked and impact childrens function. In actual it has always been common knowledge that the quality of education; opportunities for personal growth also access to resources are directly dependent on socioeconomic factors which have also remained importance in measuring childrens development. Children coming from socioeconomically disadvantaged backgrounds will face more difficulties in achieving academic success and integration into the social sphere than their peers originating from families with better socioeconomic status. Similarly, parents’ involvement plays a vital role in the nourishment of children. This dimension is in line with notions of both parental support, supervision and active engagement, as they each relate to a childs educational-e x tracurricular life. Nearly all studies reveal that increased parental involvement has been linked to more favorable academic performance, better-developed socioemotional skillsets and greater general health in children. “But the critical fact we discovered was that there is a complex interplay between socioeconomic status (SES) and parental involvement. Both factors could play a role in the appearance and severity of functional problems driven by children. So, for example, parents who come from a low SES backgrounds may have less resources and time to invest in their child’s education and well-being and even make things worse in the case of functional difficulties. The underlying biological, psychological, and social mechanisms by which SES and parental involvement moderate associations with children’s functional ability are not well understood. Therefore, the present study seeks to fill this gap in literature answering whether and how SES and parental involvement interact with each other for affecting children’s functional difficulties. “Our analysis of this linkage intends to present a comprehensive understanding of the complex dynamics between children’s functional limitations, parental involvement, and socioeconomic status”.
Generalized Transmuted Exponential Distribution
(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) BILAL MAJEED; CIIT/FA19-BST-008/LHR; Mr. Salman Abbas; LHR TP 9942
In this study, we use the Transmuted Family of distributions to develop a novel generalized exponential model. Transmuted Exponential distribution is the name of the suggested distribution. For the proposed distribution, moments, generating functions, reliability functions, among other mathematical aspects, are explored. The maximum likelihood approach is considered to estimate the distribution parameters. The use of the under study distribution in real-world scenarios is then explained. The proposed family can be used for the generalization of the classical models.
Development Of Calibration Log Estimator to Estimate Population Mean Using Randomized Response Technique
(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Rehmina; CIIT/FA19-BST-011/LHR; Dr. Riffat Jabeen; LHR TP 9944
Calibration method is a useful method in daily life meanwhile it allows us to gather a single sample without repeating the process. In the presence of sensitive information, we calculate the variation of population with the help of calibration method. We proposed calibration log ratio estimator by using the method of (Jabeen, et al. 2022) in the presence of sensitive data.
Estimation of Population Mean Using Estimator Based on Auxiliary Variable in Simple Random Sampling
(2020-04-01) Umme Habiba; CIIT/FA19-BST-007/LHR; Dr. Aamir Sanaullah; LHR TP 9951
Survey sampling is a well-established methodology employed to choose a sample of individuals from a larger population. The primary objective of this study is to estimate the population mean efficiently, by employing a comprehensive approach. To achieve this, we proposed a generalized estimator up to first degree of approximation by use of one auxiliary variable under simple random sampling framework. By deriving expressions for both bias and mean square error (MSE) of the proposed generalized estimator, we are able to ascertain its effectiveness. Remarkably, our analysis reveals that the proposed generalized estimator outperforms. Furthermore, we obtained the minimum MSE of the proposed estimator, and empirical studies demonstrated that our estimator outperform than the existing estimator found in the literature in terms of efficiency. Finally it is shown that the proposed generalized estimator efficiently work.
Spatial and Temporal Analysis of Drought
(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Muhammad Furqan Ahmad; CIIT/FA19-BST-002/LHR; Dr. Mian Muhammad Farooq; LHR TP 9938
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.
Statistical Identification of Factors Responsible for Rice Yield: Regression Analysis Approach
(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Muhammad Faheem Javaid; CIIT/FA19-BST-009/LHR; Dr. Aamir Sanaullah; LHR TP 9944
The importance of agriculture in our economy is underscored by the fact that it provides essential food supplies to meet the needs of our growing population. In Pakistan, agriculture is a vital contributor to our economic growth, Accounting for 22.7% of the GDP and employing approximately 37.4% of the Labor force. The rice ranked at 3rd place with 5.03 billion metric tons production worldwide. Pakistan came at 9th place all over the world in producing milled rice with a production of 9.32 million metric tons, rice contributes 2.4% to the value addition and 0.5% to the GDP. In this study we have collected data of Rice yield from Agriculture Department with various factors that contribute in the yield of rice. Then we use regression approach to identify the factors that are contributing in the rice yield significantly and the factors that contributing insignificantly. From the multiple linear regression, we got the R2 = 58.1% and Adjusted R Squared = .553. And then we see that, some predictor variables were found to be statistically significant while others were not as they are important for the rice yield. We suspected multicollinearity and applied factor analysis to address it. Factor analysis is applied to the independent variables, generating factors that were then used in a multiple regression analysis. The results of this analysis showed an improvement over the previous model, by making factors from all the independent variables show that all the factors are now contributing significantly in the model and the R2 has also improved from 58.1% to 68.7%.
Drought Analysis using Transmuted Weibull Distribution
(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Ali Hassan; CIIT/FA19-BST-005/LHR; Dr. Mian Muhammad Farooq; LHR TP 9940
The study aims to predict the drought analysis using monthly rainfall and temperature data. Over the past years drought is becoming important factor that is affected by climate changes in Pakistan. In this study we analyze the impact of drought in Punjab Districts. For this purpose, firstly data collected by Pakistan Metrological Department of Punjab Districts for the years 1993 to 2022 and then further competitive strategy analysis that fits our analysis or predictions are sought and critically reviewed. Then the chosen parts from strategy analysis are applied for the graphical presentation. Firstly, Applying Standardized Precipitation Index based on precipitation data by fitting transmuted Weibull distribution from the year 1993 to 2022 of each District (Bahawalnagar, Bahawalpur, Jehlum, Jhang, Lahore, Sialkot, Sargodha, Faisalabad, and Multan) to get know about classification of drought against each observed precipitation values and understand the impact of precipitation on drought. Transmuted Weibull Distribution is fitted on precipitation data to normalize it as SPI is calculated after fitting distribution on it. Further to identify trends of drought SPI calculated at different time scales by moving average of Three months, six months, and Twelve months to find SPI values and then these values are classified according to their drought conditions as moderate, severe, extreme near to normal, slightly wet, and extreme wet. Secondly applying Standardized Anomaly Index is another index that is widely used for drought analysis based on temperature data. SAI is calculated against each District (Bahawalnagar, Bahawalpur, Jehlum, Jhang, Lahore, Sialkot, Sargodha, Faisalabad, and Multan) from 1993 to 2023. By SAI values we can analyze the impact of temperature on drought. SAI values are shown in graphical form below in Chapter Results, that shows the trend and the SAI values against each year of a particular District.
ANALYSIS OF RISK FACTORS CAUSING OBESITY IN YOUTH
(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Muhammad Noman Sabir; CIIT/FA19-BST-013/LHR; Nasir Inayat; LHR TP 9947
This cross-sectional study examined the problem of overweight and obesity among students at COMSATS University, Lahore Campus. A random sample of 120 youths was surveyed using a well-constructed questionnaire to identify significant risk factors associated with weight issues. The students' BMI was used to assess their weight status. Cross-tabulation and multiple linear regressions were performed to analyze the data. The results showed that waist circumference, birth weight, meals during TV viewing, time spent on sedentary activities, celebration with food, parents' BMI, and breakfast skipping were positively linked to obesity. Conversely, vegetable consumption, fruit consumption, and feeling sluggish due to overweight were negatively associated with obesity. These findings emphasize the importance of addressing multiple factors in tackling overweight and obesity among youth. Implementing interventions targeting these risk factors could lead to effective prevention and management of weight problems.
Construction of Calibration Log Ratio Estimator to Estimate Population Variance
(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Khafiza Afzal; CIIT/FA19-BST-003/LHR; Dr. Riffat Jabeen; LHR TP 9938
Calibration is frequently used to improve the population parameter estimation’s accuracy using auxiliary data. In our study, we have introduced the calibration and the calibration log variance estimator for estimating the population variance. The study proposes the calibration variance log estimators using chi square distance measure and different calibration constraints respectively. Our findings indicate that the suggested calibration variance estimator performed better than the existing estimator.
Generalized Transmuted Weibull Distribution
(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) MOHSIN QUDDUS; CIIT/FA19-BST-012/LHR; Salman Abbas; LHR TP 9946
In this research, we introduce a new generalized Weibull distribution using a new Transmuted family. An account of statistical characteristics of the generalized model is discussed in detail. Estimation of the model parameter is followed by method of maximum likelihood. A real-life application is presented to illustrate the applicability of the derived model. This new family of distribution can be utilized by researchers for developing generalized distributions in the future.
Transmuted Marshall Olkin Modified Burr-III Distribution
(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Ali Zain; CIIT/FA19-BST-004/LHR; Dr. Mian Muhammad Farooq; LHR TP 9939
Transmutation of classical probability distributions play a significant role in real life modeling. In this work, we develop a new Transmuted Marshall Olkin Modified Burr-III distribution. The proposed model is named Transmuted Marshall Olkin Modified Burr-III distribution (TMOMBIIID). Several statistical characteristics of TMOMBIIID such as survival function and hazard rate, are discussed. The Maximum likelihood method is followed for the estimation of model parameters.
Understanding Household Characteristics and Wealth Distribution
(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Husnain Ali Sher; CIIT/FA20-BST-005/LHR; Dr. Muhammad Noor-ul-Amin; LHR TP 9950
The great thing about this research is that it provides in-depth analysis regarding household dynamics, socio-economic disparities, and the impact of modern amenities on daily life within a community. Using several sophisticated machine learning techniques, statistical modeling, and rigorous data analysis, we attempted to identify the characteristics of these households and their corresponding socio-economic environment. This is followed by the study’s objectives, and how crucial household characteristics are in the context of today’s world. It is concerned with the spread and import of houses having internet connections, refrigerators, and televisions. The study applies machine learning models based on neural networks and SVM for regression as follows. international sharing that provides the results and discussion of prediction for household characteristic ownership of modern amenities as we might expect, there was a strong correlation between the wealth of the household and possessions: the richer they were, the more amenities people had. The educational qualification of the household head also continued to be a significant determinant in terms of socio economic achievements and ownership of modern amenities. The most important and outstanding characteristics are education for linear ones and households. Multiple regression analysis was used to predict outcomes. The model reveals that the highest levels of education for household heads indicate positive signs of socioeconomic status and ownership of modern amenities. The machine learning models often gave me little extra insights Nevertheless there are a few limitations and challenges since family dynamics in the neural network model may be overfitting. These models helped to explore predictors of household behavior leading to understanding socio-economic factors on modern facilities ownership. This research highlights the importance of contemporary amenities in households and their association with socio-economic status. Our study findings underscore the importance of working not only to further educational opportunities but also to be more active in ensuring access and education around digital connectivity, which is a critical stepping-stone for fairer development and improved quality of life.
Determinants of Child Mortality in Punjab, Pakistan
(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Kashaf Zahra; CIIT/FA20-BST-006/LHR; Dr. Muhammad Noor-ul-Amin; LHR TP 9951
This research project examines the key determinants of child mortality in Punjab, Pakistan, focusing on factors such as birth order, mother’s age at birth, birth interval, premature birth, and multiple births. These findings indicate that firstborn and higher-order children exhibit higher mortality rates, which are attributed to inexperienced parenting in the case of firstborns and the dispersion of resources among siblings for higher-order children. The study showed that children born to mothers aged between 20-34 years had the highest survival rates than children born to mothers who are teenagers or mothers above 34 years. This means that the families mothers give birth within the age interval 20-34 are more likely to have low mortality rates hence the need to encourage family planning. It was also observed that both premature and multiple births are associated with high mortality rates hence there is a need to enhance quality perinatal and neonatal services. It is recommended that the Ministry of Health focuses on streamlined health policies, enhanced awareness of parents, and improved supply of resources to decrease infant mortality and promote general child health in the area. Integrated approaches, awareness campaigns, and the improvement of education and health care as well as the establishment of favorable policies are indispensable to tackle the multifaceted problem of child mortality.
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.
INTERNSHIP REPORT ON BUREAU OF STATISTICS, GOVERNMENT OF PUNJAB, LAHORE
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Muhammad Shehroz; CIIT/FA21-BST-025/LHR; Dr. Tajamul Hussain; LHR TP 9934
The Bureau of Statistics, Government of Punjab, serves as the primary repository and hub for statistical data activities in the province, tasked with collecting, analyzing, and disseminating statistical information through various publications and media. As it is attached to the Planning and Development Department, BOS operates in accordance with standards set by the National Statistical Council. Its key functions are to collect provincial- level data, coordinate and support statistical activities across the province, liaise with the Federal Statistical System, and prepare and disseminate provincial indicators through institutional sources and new censuses/surveys. With its Head Office in Lahore and an extensive network of 9 divisional and 15 district field offices, BOS, Punjab ensures comprehensive coverage across the province. Upon gaining independence in 1947, Pakistan faced the challenge of a decentralized statistical system, where data production was closely tied to government administration rather than a centralized statistical authority. Before establishing the Bureau of Statistics, statistical functions were dispersed across various government departments, with each department's statistical cell possessing differing levels of strength, technical expertise, and skills. However, there was no centralized agency to coordinate and harmonize their activities, resulting in a lack of cohesion and consistency in statistical data collection and analysis. Recognizing the system's limitations, the Pakistan Government established the Central Statistical Office (CSO) in 1950 as an attached department of the Economic Affairs Division, based on the recommendations of the Statistical Reorganization Committee. The CSO aimed to coordinate the country's statistical activities and meet its growing data needs. As development planning gained emphasis and demand for statistical data increased, the Planning Commission recommended expanding CSO's activities, leading to the establishment of Provincial Bureaus of Statistics in West Pakistan and East Pakistan, as advised by the IBRD Mission. The Bureau of Statistics was subsequently established in October 1957 within the Power, Irrigation & Development Department of the Government of West Pakistan, tasked with providing a continuous source of statistical data, enhancing provincial statistics, and disseminating information through publications. The Bureau was later integrated into the Planning and Development Department on January 31, 1959, and declared an attached department on July 1, 1973.
RNN for Time series Forecasting Using Google Stock Prices
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Sharjeel Ahmed; CIIT/FA20-BST-011/LHR; Dr. Mian Muhammad Farooq; LHR TP 9955
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.
EBiz Lounge (Private) Limited
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Ansa Bibi; CIIT/FA21-BST-008/LHR; Dr. Tajammul Hussain; LHR TP 9929
This internship report reflects the expert encounters and bits of knowledge acquired at EBiz Lounge Private Limited. As a Statistics student at COMSATS University, Islamabad, Lahore campus this internship offered an important chance to apply hypothetical information in a certifiable setting. The active openness in the online business, especially through association with the eBay stage, extended the comprehension of computerized commercial centers and upgraded specialized and scientific skills. The essential goal of the internship was to obtain useful involvement in overseeing item postings on eBay, advancing search engine optimization(SEO) techniques, and adding to deal development. Errands included item posting improvement, leading statistical surveying, and breaking down deals execution. Every obligation added to the proficient turn of events and gave further experiences in e-commerce dynamics. Challenges, such as adapting to changing algorithms and managing multiple priorities, offered meaningful learning opportunities. This report sums up the encounters, information acquired, and skills created during the internship. It involves the tasks which are completed in the internship, challenges I faced, and the possible solutions to get successful outcomes. Ideally, this report will act as a helpful asset for understudies and experts looking to comprehend the powerful web-based business scene and the worth of viable involvement in cultivating proficient development.
INTERNSHIP REPORT ON BUREAU OF STATISTICS, GOVERNMENT OF PUNJAB, LAHORE
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Sania Khalid; CIIT/FA21-BST-014/LHR; Dr. Tajamul; LHR TP 9932
The Bureau of statistics (BOS) of the Punjabi government is Official government statistics provider in the province. BOS is also charged with the responsibility of receiving collecting, assessing, and disseminating statistical data through electronic media and in specific periodical publications that it comes up with. It is an associated department of the Planning and Development Department which primarily focuses on the issues of youth’s participation in political leadership and governance. It works in conjunction with the Federal Statistical System; it formulates statistical initiatives, supervises provincial level data acquisition and calculates provincial scores using surveys and censuses. Seven Division/ nine District Field Offices of BOS along with Lahore headquarters are importance components of development planning and decision making in Punjab. BOS was originally set up in 1957 while in 1959 it was placed under the Power, Irrigation & Development Department of West Pakistan’s Planning and Development Department. Then it developed into a more serious form of a disease that does not have any well-defined treatment to this day. This development was part of a broader effort to address the shortcomings of Pakistan’s decentralized statistical system and to enhance the coordination and expansion of statistical activities across the country.
INTERNSHIP REPORT ON BUREAU OF STATISTICS, GOVERNMENT OF PUNJAB, LAHORE
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Muhammad Shayan; FA21-BST-005; Dr. Tajamul Hussain; LHR TP 9928
The Bureau of Statistics Punjab, Government of Punjab, is in charge for the gathering, processing and spreading statistical data via publications and electronic platforms. Being an associated department of the Planning and Development Department, Government of Punjab, the main responsibilities of Bureau of Statistics Punjab is collecting provincial level data, coordinating and supporting in different statistical activities across Punjab, working with the Federal Statistical system, and preparing and disseminating provincial data through institutional sources also conducting new censuses and surveys, These responsibilities are guided by the National Statistical Council. The Bureau of Statistics Punjab is headquartered in Lahore, with 9 divisional and 7 district field offices throughout the province
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.