http://localhost:80/xmlui/handle/123456789/17349 2026-04-04T02:33:15Z 2026-04-04T02:33:15Z S. Mudassiri J. Muhammad J. Akbai T. Mir R. Zeeshan http://localhost:80/xmlui/handle/123456789/18812 2023-03-14T03:36:49Z 2016-06-14T00:00:00Z

Title: Co-Design of Dual-Band Low Noise Amplifier Operating in 900MHz/1800MHz Bands for Multi-standard Wireless Receiver Authors: S. Mudassiri; J. Muhammad; J. Akbai; T. Mir; R. Zeeshan Abstract: In this paper the design of a fully concurrent dual-band (900/1800MHz) low-noise amplifier (LNA) is presented, the main aim is to bring the noise figure below 3dB to improve the performance of modem receivers. Two single band LNAs operating at GSM 0.9GHz and Digital Cellular System (DCS) 1.8GHz are separately designed using traditional method firstthen both single-band matching networks aremerged, one dual-band matching network (MNs) of the dual band LNA is designed at (900MHz and 1800MHz). This is a single stage amplifier. The dual band LNA is designed to provide low noise figure. The fully concurrent LNA circuit designed using BFG520 Transistor technology, and simulated in Advance Design System (ADS) of version 2009A. For use in multi-standard wireless receiver frontend the proposed design is very useful because the noise figure obtained is suitable for the better performance. The simulation results show that single band LNA at 900 MHz gives the Noise figure of 1.2dB while at 1800MHz it is increased to 2.6dB, the dual band design provides the Noise figure of 1.19dB and 2.71dB for 900MHz and 1800MHz respectively, using 100mA current from 9V power supply with the power consumption of 0.9 Watt.

2016-06-14T00:00:00Z N. Irtiza H. Farooq http://localhost:80/xmlui/handle/123456789/18810 2023-03-14T03:36:17Z 2016-06-12T00:00:00Z

Title: Classification of Brain States using Subject-Specific Trained Classifiers Authors: N. Irtiza; H. Farooq Abstract: One of the key components to develop a usable Electroencephalography (EEG) based Brain Computer interface (BCI) is the efficient classification of EEG patterns using Machine Learning classifiers. This paper presents a comparison of Linear Discriminant Analysis (LDA), Naïve Bayes and Decision Tree classifiers by applying to the EEG data. The classifiers are applied on BCI Competition III: Dataset V that consists of three cognitive tasks, namely, right and left hand imagery movement and the imagination of any word starting from a given random letter. The BCI experiments for this data have been performed with three subjects. For subjects 1 and 2, the Naïve Bayes classifier provides best results while for subject 3 the maximum accuracy is achieved from LDA classifier. In order to improve the accuracy further, it has been proposed to apply combination of classifiers based on Multiple/Ensemble Classifier System concept on data for single subject with different sessions of data recording. By combining the classifiers LDA and Decision Tree, maximum accuracies of 81%, 70% and 56% for subjects 1, 2 & 3 respectively have been achieved that are comparable with the accuracies achieved by the winner of the competition. It is concluded that instead of employing single classifier, the approach for using combination of classifiers significantly improves the performance of a BCI system.

2016-06-12T00:00:00Z Method M. Aslam S. N. R. Shah S. H. Otho http://localhost:80/xmlui/handle/123456789/18808 2023-03-14T03:35:59Z 2016-05-11T00:00:00Z

Title: Casagrande Liquid Limit Testing Of Jamshoro Soil By One Point Authors: Method M. Aslam; S. N. R. Shah; S. H. Otho Abstract: The Liquid limit (LL) tests are considered essential to determine the index properties of soil. Casagrande liquid limit test is one of these tests and universally recognized for soil testing. The purpose of this research work is to introduce the constant values of index (e) and Number of Blows for A-7-6 (AASHTO Classification) clayey shale type soils using one point formula. 100 samples ofA-7-6 soil were collected from Jamshoro (Pakistan) zone and multi point Casagrande liquid limit laboratory tests were performed. After obtaining test results, samples were squeezed out with appropriate range of LL covering maximum number of samples. Suitable range of number of blows was chosen and the most appropriate index (e) value for selected soil samples was calculated. The experimental results were compared with one point formula results. The reliability of LL between experimental results and one point formula results exhibited excellent relationship.

2016-05-11T00:00:00Z M. Ullahl A. M. Khan R. Nawaz R. Akhtar http://localhost:80/xmlui/handle/123456789/18805 2023-03-14T03:33:27Z 2016-06-10T00:00:00Z

Title: Process Improvement for PET Bottles Manufacturing Company Using Six Sigma Approach Authors: M. Ullahl; A. M. Khan; R. Nawaz; R. Akhtar Abstract: Rejection in production processes cannot be ignored in industries in general, and in manufacturing organizations in particular. Six sigma has been considered an organized and scientific approach for the last few decades in order to reduce the number of rejections in processes. This paper has focused the injection modeling process in PET bottles manufacturing industry in Pakistan. The paper aims to reduce the number of rejected products produced during the injection molding process and highlight the significant factors and their level that severely affect the molding process. Different type of defects were observed in the injection molding process. Statistical approach using hypothetical analysis and experimental design techniques were used to conclude significant factors and their levels. Injection pressure, melting temperature, and resin type were observed as the most significant factors that affect the number of defective products produced during the PET bottles manufacturing. The joint interaction effect of pressure and temperature was also significant in comparison to all other interaction effects during this process.

2016-06-10T00:00:00Z