جدوں اویس دا ٹُٹا دند
ہوئے حضوری وچ پسند
رہن عاشق توں پاسے پاسے
ہور نہیں دیندے کوئی گزند
عشق توں رہندے دور دراڈے
جیہڑے بندے عقل مند
سوہنے ڈگدے سوہنیاں اتے
کر کے ساڈا ساہ بند
ہمدردی تے خدمت سیوا
ایہو نیکاں دی ہے ، ھند
دکھاں درداں دے جو ساتھی
دنیا اتے بندے چند
ڈرے حنیف خدا توں خبرے
کیہڑا اوہنوں رنگ پسند
The extract is that the plastic surgery is legitimate for medical treatment. Any kind of transformation in the creation of Allah is illegitimate. For women the removal of extra hair the usage of different kind of creams etc for fairness is legitimate. The transformation of inborn deficiency is legitimated. In case of deception and for the sake of Satan the illegitimate transformation in human body which is bestowed by ALLAH is considered as ingratitude and ungratefulness to ALLAH which is abominable and invalid.
The thesis is aimed to explore ICA to comprehend massive data fully. Financial time series’ data from KSE is used to compute ICs with JADE, SOBI, and FastICA algorithms and a deep insight of the series is targeted through study of the internal structure. Attempts from different directions are made to achieve the goal. Ordering of the ICs to define their priority in retention is addressed. A new regression based method is successfully introduced where regression coefficients obtained by regressing the original series on ICs are used. The magnitudes of the mixing coefficients are compared with regression coefficients for their compatibility to determine the order of the ICs. A novel approach, based upon comparing original and reconstructed series gauged through is proposed to decide how many ICs should be retained to reconstruct the series successfully. Identification of clusters is attempted to reduce the dimensionality in natural way. Two ICA based approaches namely adapted estimated mixing coefficients approach and ranked approach have been proposed and demonstrated. The first approach is based upon sum of squares of mixing coefficients whereas the second approach uses rank order of at predefined threshold levels. Internal and external structures of clusters are also explored through different metrics. Moreover, compatibility of the clusters is contrasted with the available grouping mechanisms. Keywords: Dimension Reduction; Financial Time Series; Ordering ICs; Reconstruction of Series; Regression; Clustering