Faisal Afzal Siddiqui | University of Karachi (original) (raw)
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International Institute of Information Technology, Hyderabad
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Papers by Faisal Afzal Siddiqui
Advanced Engineering Informatics, 2020
Instrumentation is beneficial in civil engineering for monitoring structures during their constru... more Instrumentation is beneficial in civil engineering for monitoring structures during their construction and operation. The data collected can be used to observe real-time response and develop data-driven models for predicting future behaviour. However, a limited number of sensors are usually used for on-site civil engineering construction due to cost restrictions and practicalities. This results in relatively small raw datasets, which often contain errors and anomalies. Interpreting and making judicious use of the available dataset for developing reliable predictive model represents a significant challenge. Therefore, it is essential to pre-process and clean the data for improving their quality. To date, little investigation has been performed in the application of such data cleaning methods to geotechnical engineering datasets collected from full-scale sites. The purpose of this study is to apply simple and effective data pre-processing techniques to site-data collected from a highway embankment constructed on a sequence of soil layers of different physical make-up and non-linear consolidation characteristics. Various cleaning methods were applied to magnetic extensometer data collected for monitoring settlement within foundation soils beneath the embankment. PCA was used to explore raw data, identify and remove outliers. Numerous filtering and smoothing methods were used to clean noise in the data and their results were further compared using RMSE and NMSE. The methods adopted for data pre-processing and cleaning proved very effective for capturing the raw settlement behaviour on site. The findings from this study would be useful to site engineers regarding complex decision-making relating to ground response due to embankment construction. This also has positive prospects for developing dynamic prediction models for embankment settlement.
The performance of any communication system is assessed by its bit error rate (BER). Energy to No... more The performance of any communication system is assessed by its bit error rate (BER). Energy to Noise ratio plays an important role in evaluation of a communication system. The application of chaos based communication system is very popular. To check the relationship between energy to noise ratio and BER, WCDMA downlink simulation model as per 3gpp specification is used with chaos codes along OVSF spreading codes. Simulation is done in the presence of an additive white Gaussian noise (AWGN) channel along with QPSK modulation. The simulations and Bit Error Rate (BER) evaluation with respect to Energy-To-Noise ratio are performed using MATLAB. The researcher developed the regression model to find the effect of chaotic modulation on bit error rate performance in direct sequence spread spectrum communication.
Journal of Management Thought, 2008
The aim of this article is to provide an introduction to conjoint analysis as a research tool, an... more The aim of this article is to provide an introduction to conjoint analysis as a research tool, and to indicate its value for analyzing consumer preference based on the value that the consumers attach to the attributes of the goods that they intend to purchase. The study involves the use of the tool of conjoint Analysis to evaluate consumer preference vis.a.vis Brand, Price Level, FM Radio, and Camera. The results of the study indicate that the most important attribute behind consumer preference for mobile phones was Brand, followed by Price, then Camera, and finally FM Radio.
Advanced Engineering Informatics, 2020
Instrumentation is beneficial in civil engineering for monitoring structures during their constru... more Instrumentation is beneficial in civil engineering for monitoring structures during their construction and operation. The data collected can be used to observe real-time response and develop data-driven models for predicting future behaviour. However, a limited number of sensors are usually used for on-site civil engineering construction due to cost restrictions and practicalities. This results in relatively small raw datasets, which often contain errors and anomalies. Interpreting and making judicious use of the available dataset for developing reliable predictive model represents a significant challenge. Therefore, it is essential to pre-process and clean the data for improving their quality. To date, little investigation has been performed in the application of such data cleaning methods to geotechnical engineering datasets collected from full-scale sites. The purpose of this study is to apply simple and effective data pre-processing techniques to site-data collected from a highway embankment constructed on a sequence of soil layers of different physical make-up and non-linear consolidation characteristics. Various cleaning methods were applied to magnetic extensometer data collected for monitoring settlement within foundation soils beneath the embankment. PCA was used to explore raw data, identify and remove outliers. Numerous filtering and smoothing methods were used to clean noise in the data and their results were further compared using RMSE and NMSE. The methods adopted for data pre-processing and cleaning proved very effective for capturing the raw settlement behaviour on site. The findings from this study would be useful to site engineers regarding complex decision-making relating to ground response due to embankment construction. This also has positive prospects for developing dynamic prediction models for embankment settlement.
The performance of any communication system is assessed by its bit error rate (BER). Energy to No... more The performance of any communication system is assessed by its bit error rate (BER). Energy to Noise ratio plays an important role in evaluation of a communication system. The application of chaos based communication system is very popular. To check the relationship between energy to noise ratio and BER, WCDMA downlink simulation model as per 3gpp specification is used with chaos codes along OVSF spreading codes. Simulation is done in the presence of an additive white Gaussian noise (AWGN) channel along with QPSK modulation. The simulations and Bit Error Rate (BER) evaluation with respect to Energy-To-Noise ratio are performed using MATLAB. The researcher developed the regression model to find the effect of chaotic modulation on bit error rate performance in direct sequence spread spectrum communication.
Journal of Management Thought, 2008
The aim of this article is to provide an introduction to conjoint analysis as a research tool, an... more The aim of this article is to provide an introduction to conjoint analysis as a research tool, and to indicate its value for analyzing consumer preference based on the value that the consumers attach to the attributes of the goods that they intend to purchase. The study involves the use of the tool of conjoint Analysis to evaluate consumer preference vis.a.vis Brand, Price Level, FM Radio, and Camera. The results of the study indicate that the most important attribute behind consumer preference for mobile phones was Brand, followed by Price, then Camera, and finally FM Radio.