The maximal commutative subalgebras containing only Toeplitz matrices have been identified as generalized circulants. A similar simple description cannot be obtained for block Toeplitz matrices. We introduce and investigate certain families of maximal commutative algebras of block Toeplitz matrices.
Affordable Housing is a critical issue in many developing countries that impacts their potential for sustainability and socio-economic development. Lack of affordable housing, slower growth of housing stock, and aging housing conflates numerous other problems in Pakistan, including overcrowding, poor indoor air quality, prevalence of preventable diseases, and development of slums and katchi abadies, etc. These challenges lessen living standards in many areas. Unaffordable housing forces low income families in urban areas to live in dilapidated areas. An increase in the construction of affordable housing is needed to mitigate housing affordability challenges in Pakistan. Setting aside land quotas for low-income families in housing development schemes is not sufficient because the households still lack the means to construct housing. This paper attempts to identify the causes of unaffordable housing and solutions for its provision.
In this article we present an algorithm to compute the incidence matrix of the resolution graph, the total multiplicities, the strict multiplicities and the Milnor number of a reduced plane curve singularity and its implemetation in Singular
Muhammad Ibn Ibrahimy, Rezwanul Ahsan and Othman Omran Khalifa
This paper presents an application of artificial neural network for the classification of single channel EMG signal in the context of hand motion detection. Seven statistical input features that are extracted from the preprocessed single channel EMG signals recorded for four predefined hand motions have been used for neural network classifier. Different structures of neural network, based on the number of hidden neurons and two prominent training algorithms, have been considered in the research to find out their applicability for EMG signal classification. The classification performances are analyzed for different architectures of neural network by considering the number of input features, number of hidden neurons, learning algorithms, correlation between network outputs and targets, and mean square error. Between the Levenberg-Marquardt and scaled conjugate gradient learning algorithms, the aforesaid algorithm shows better classification performance. The outcomes of the research show that the optimal design of Levenberg-Marquardt based neural network classifier can perform well with an average classification success rate of 88.4%. A comparison of results has also been presented to validate the effectiveness of the designed neural network classifier to discriminate EMG signals.
Ahsan Nazir, Tanveer Hussain, Ali Afzal, Sajid Faheem, Waseem Ibrahim and Muhammad Bilal
The aim of this study was to develop statistical models for predicting the air permeability and light transmission properties of woven cotton fabrics and determine the level of correlation between the two parameters. Plain woven fabrics were developed with different warp and weft linear densities, ends per inch and picks per inch. After desizing, scouring, bleaching, drying and conditioning, the air permeability and light transmission properties of the fabric samples were determined. Regression analysis results showed statistically significant effect of the fabric ends, picks and warp linear density on both the fabric air permeability and light transmission. Correlation analysis was performed to analyze the relation between the fabric air permeability and light transmission. A linear equation was also formulated to find the fabric air permeability through transmission of light intensity. A fitted line plot between the air permeability and light transmission exhibited significant correlation with R-sq. value of 96.4%. The statistical models for the prediction of fabric air permeability and light transmittance were developed with an average prediction error of less than 7%.
Ahsan Nazir, Tanveer Hussain, Qummer Zia and Muhammad Ali Afzal
Cotton is one of the most commonly used fibres for making knitwear. Some of the limitations of pure cotton knits include their tendency to shrink, relatively limited durability, and poor wash and wear properties. In order to overcome these limitations knitwear are also produced from polyester and cotton blends, however, at the cost of reduction in comfort properties. The objective of this study was to improve the thermo-physiological comfort properties of knits made from polyester/cotton (P/C) blends through simple chemical and biological treatments. The specimens of P/C knits were subjected to treatments with caustic soda solutions and the cellulase enzymes. It was found that the air permeability and perspiration management properties of P/C knits can be significantly improved by appropriate caustic treatment. However, the biological treatment with cellulase enzymes is comparatively less effective in making any improvement in the thermo-physiological comfort properties of P/C knits.
Munir Ashraf, Muhammad Irfan Siyal, Ahsan Nazir and Abdur Rehman
Functionalization of textile fabrics with metal oxide nanoparticles can be used to add antibacterial and moisture management properties to them. Current work focuses on the development of these properties on polyester/cotton woven fabrics by treating them with zinc oxide nanoparticles for workwear and sportswear applications. Zinc oxide nanoparticles, prepared by sol-gel method, were applied on fabric samples, which were then tested for antibacterial and moisture management properties using standard test methods AATCC 147 with Staphylococcus aureus and AATCC 195, respectively. It was found that application of ZnO nanoparticles improved both these properties with smaller particle imparting larger effects on both of them.
Muhammad Ahsan Binyamin, Junaid Alam Khan and Hasan Mahmood
In this article we characterize the ideal unimodular singularities in terms of their invariants. On the basis of this characterization we give an implementation of a classifier for ideal unimodular singularities in the computer algebra system SINGULAR.
Deeba Afzal, Muhammad Ahsan Binyamin and Faira Kanwal Janjua
The aim of the article is to describe the classification of simple isolated hypersurface sin- gularities over a field of positive characteristic by certain invariants without computing the normal form. We also give a description of the algorithms to compute the classification which we have implemented in the Singular libraries classifyCeq.lib and classifyReq.lib. 1 Int