Mehran University Research Journal of Engineering and Technology

8

Authors: Memon S., Bhatti S., Abro F.R.

This paper investigates the task of SR (Speaker Recognition) for the state-of-the-art techniques. The paper initially presents the technical description of automatic SR, followed by the comparative analysis of a number of methods available for feature extraction and modeling. Based on this analysis the NIST 2001, NIST 2002, NIST 2004 and NIST 2006 Speaker recognition corpora are used to investigate the state of the art feature extraction and modeling techniques. The state of the art technique for feature extraction is delta MFCC ( Mel Frequency Cepstral Coefficients) and for modeling is GMM (Gaussian Mixture Models) based on EM (Expectation Maximization). Further in this paper the details about the enrollment/training and recognition/testing is also presented. For different stages of SR systems the conventional methods are summarized

8

Authors: Shah A.K., Syed F.A.S., Memon H.R.

The study aimed to improve the effectiveness of dyes and pigments wastewater treatment. Hybrid system of adsorption and coagulation was applied for the reduction of COD, color, turbidity and TSS. Activated carbon adsorbent was prepared from a waste of sugar industry boiler. It was processed through physicochemical treatment with sulfuric acid following grinding, sieving, washing and drying unit operations. Combined wastewater of dyes and pigments manufacturing plant was treated with a hybrid process of coagulation and adsorption. FeCl 3, FeSO 4and Alum coagulants were tested individually and found them less effective. It was revealed that FeCl 3 coagulation, adsorption and hybrid process reduced COD (41, 51 and 54%), Color (67, 70 and 89%), turbidity (69, 71 and 90%) and TSS (82, 93 and 97%) respectively. Combination of FeCl3 -SBFA (Sugarcane Bagasse Fly Ash) proved 90% efficient in removal than coagulation as an individual process. 4g adsorbent dose was optimized for this hybrid process

8

Authors: Ghani U., Ali S.,Arif S.

The turbulence models play an important role in all types of computational fluid dynamics based numerical modelling. There is no universal turbulence model which can be applied in all the scenarios. Therefore, if a suitable closure model is used in a simulation work, only then the successful numerical modelling will be achieved. This paper presents the evaluation of three turbulence models in numerical modelling of open channel flows having beds comprising of two parallel strips, one being smooth and the other one being rough. The roughness on the rough side of the channel was created with the help of gravels. The turbulence models tested for their suitability in this case were Reynolds stress model, k-?model and RNG based k-?model. A structured mesh was used in this simulation work. Grid independence test was also conducted in the simulation. The evaluation of the turbulence models was made through the primary velocity contours and secondary velocity vectors over the cross section of the channel. It was revealed that Reynolds stress model simulated the flow behaviour successfully and results obtained through this model matched very closely to that of the experimental data whereas k-?model and RNG based k-? model failed to reproduce the flow field successfully. These results will be helpful for CFD (Computational Fluid Dynamics) modellers in correct selection of the turbulence model in these types of channels

10

Authors: Memon I.A., Kalhoro M.S., Channa N.

Cross-bicoherence analysis is one of the important nonlinear signal processing tools which is used to measure quadratic phase coupling between frequencies of two different time series. It is frequently used in the diagnosis of various cognitive and neurological disorders in EEG (Electroencephalography) analysis. Volume conduction effects of various uncorrelated sources present in the brain can produce biased estimates into the estimated values of cross-bicoherence function. Previous studies have discussed volume conduction effects on coherence function which is used to measure linear relationship between EEG signals in terms of their phase and amplitude. However, volume conduction effect on crossbicoherence analysis which is quite a different technique has not been investigated up to now to the best of our knowledge. This study is divided into two major parts, the first part deals with the investigation of VCUS (Volume Conduction effects due to Uncorrelated Sources) characteristics on EEG-cross-bicoherence analysis. The simulated EEG data due to uncorrelated sources present in the brain was used in this part of study. The next part of study is based upon investigating the effects of VCUS on the statistical analysis of results of EEG-based cross-bicoherence analysis. The study provides an important clinical application because most of studies based on EEG cross-bicoherence analysis have avoided the issue of VCUS. The cross-bicoherence analysis was performed by detecting the change in MSCB (Magnitude Square CrossBicoherence Function) between EEG activities of change detection and no-change detection trials. The real EEG signals were used

10

Authors: Channa S., Memon T.D., Halepoto I.A.

In this paper, we present a thorough research to analyze the performance of the soft switches of PTCL (Pakistan Telecommunication Company Limited) in south region by taking real values from the operational systems and ratio of fault occurrence in soft switches. The major issues and shortcomings related to hardware of soft switches, network build up and protocols of SS (Soft Switch) are discussed. Performance characteristics of two soft switches (Pak Capital SS Vendor-A and Marston Rd SS Vendor-B) on the basis of key parameters including, System over view, System architecture, Hardware, Network built-up are analyzed. All parameters are compared with PTA (Pakistan Telecommunication Authority) standards and suggestions are provided to remove single point of failure to achieve 24x7 services available for the customers of PTCL. The conclusion drawn out of the research works, and suggestions provided will pave a path to increase the efficiency of soft switches, enrich the operation of the system, reduces the fault occurrence and complete isolation of the MGs/MSAN/MSAGs, improve the availability of the PTCL services to its customers and will enhance the image of the company for its valuable customers

12

Authors: Memon A.P., Uqaili M.A., Memon Z.A.

The transients in power system cause serious disturbances in the reliability, safety and economy of the system. The transient signals possess the nonstationary characteristics in which the frequency as well as varying time information is compulsory for the analysis. Hence, it is vital, first to detect and classify the type of transient fault and then to mitigate them. This article proposes time-frequency and FFNN (Feedforward Neural Network) approach for the classification of power system transients problems. In this work it is suggested that all the major categories of transients are simulated, de-noised, and decomposed with DWT (Discrete Wavelet) and MRA (Multiresolution Analysis) algorithm and then distinctive features are extracted to get optimal vector as input for training of PNN (Probabilistic Neural Network) classifier. The simulation results of proposed approach prove their simplicity, accurateness and effectiveness for the automatic detection and classification of PST (Power System Transient) types

16

Authors: Janjua A.B., Khalil M.S., Saeed M.

Utilization of hydro-power as renewable energy source is of prime importance in the world now. Hydropower energy is available in abundant in form of falls, canals rivers, dams etc. It means, there are various types of sites with different parameters like flow rate, heads, etc. Depending upon the sites, water turbines are designed and manufactured to avail hydro-power energy. Low head turbines on runof-river are widely used for the purpose. Low head turbines are classified as reaction turbines. For runof river, depending upon the variety of site data, low head Kaplan turbines are selected, designed and manufactured. For any given site requirement, it becomes very essential to design the turbine runner blades through optimization of the CAD model of blades profile. This paper presents the optimization technique carried out on a complex geometry of blade profile through static and dynamic computational analysis. It is used through change of the blade profile geometry at five different angles in the 3D (Three Dimensional) CAD model. Blade complex geometry and design have been developed by using the coordinates point system on the blade in PRO-E /CREO software. Five different blade models are developed for analysis purpose. Based on the flow rate and heads, blade profiles are analyzed using ANSYS software to check and compare the output results for optimization of the blades for improved results which show that by changing blade profile angle and its geometry, different blade sizes and geometry can be optimized using the computational techniques with changes in CAD models.