مولانا محمد اویس ندوی نگرامی
دارالمصنفین اور معارف کے حلقہ میں مولانا محمد اویس ندوی نگرامی کا نام محتاج تعارف نہیں ہے، وہ معارف کی مجلس ادارت کے رکن اور دارالمصنفین کی مینیجنگ کمیٹی کے ممبر تھے، رفیق کی حیثیت سے بھی کئی سال تک یہاں رہ چکے اور تصنیف و تالیف کے علاوہ سیرۃ النبی کی نظرثانی میں بھی انھوں نے مولانا سید سلیمان ندوی مرحوم کا ہاتھ بٹایا تھا، سید صاحب کی جوہر شناس نگاہ نے طالب علمی کے زمانہ ہی میں ان کی صلاحیت کا اندازہ کرلیا تھا، تعلیم سے فراغت کے کچھ ہی عرصہ بعد ان کو دارالمصنفین لے آئے، تصنیف و تالیف کے علاوہ وہ ان کی درسی لیاقت کے بھی معترف تھے، قرآن مجید کے مطالعہ کا شوق انہیں شروع ہی سے تھا، سید صاحب کی صحبت میں یہ ذوق اور بڑھا، یوں تو سبھی اہم تفسیریں نظر سے گزریں تھی، لیکن ابن جریر اور ابن کثیر سے زیادہ دلچسپی تھی علامہ ابن تیمیہ اور حافظ ابن قیم کے تو عاشق تھے، ان کا ذکر بڑے والہانہ انداز میں کیا کرتے تھے، اس گرویدگی کا اثر تھا کہ مختلف کتابوں سے ان کے تفسیری بیانات چن کر ایک ضخیم کتاب تیار کردی، ان کی یہ کوشش ہندوستان ہی میں نہیں، بلکہ پوری دنیا میں قدر کی نگاہ سے دیکھی گئی، اب تک کئی اڈیشن شائع کرچکے ہیں۔
علمی انہماک کے ساتھ تزکیۂ نفس اور اصلاح باطن کا بھی بڑا خیال تھا، ان کا خاندان شریعت و طریقت کی جامعیت میں ممتاز تھا، ان کے پردادا مولانا عبدالعلی حضرت شاہ علم اﷲ رائے بریلوی کے سلسلہ سے وابستہ تھے، دادا مولانا محمد ادریس بھی ایک بڑے عالم اور شیخ طریقت تھے، وہ مولانا عبدالحئی فرنگی محلی مولانا عبدالحق حقانی اور قاری عبدالرحمن پانی پتی کے شاگرد اور مولانا فضل رحمن گنج...
The Benazir Income Support Program (BISP), introduced in 2008-09, is a unique cash support scheme for economically stressed families. Its uniqueness arises from several facets. The cash transfers are provided only to women aged over 18 years and have been ever married. It is unconditional and aimed at supplementing income as opposed to alleviating poverty. It was politically neutral, given that the facility to identify potential beneficiaries was extended to all parliamentarians, irrespective of party affiliation. A set of filters, applied electronically, ensured objectivity in beneficiary selection. Disbursement mechanism was automated to ensure minimal leakage. This paper outlines the process of the preparatory work that went into designing BISP – the conceptual debates, the beneficiary identification and disbursement procedures, etc. – involving a combination of high quality research with political decision making. It also addresses the debates surrounding BISP, cites independent empirical studies that show that the parliamentarian-based beneficiary selection mechanism was efficient and equitable and did indeed cover the deserving, and also responds to the variety of criticisms. ______
This dissertation is a contribution to computer vision and its analysis. The main work of this dissertation is to develop segmentation models for texture images. Texture segmentation aims at segmenting an image composed of textures, into distinct homogeneous regions with dissimilar texture features. For this purpose, some new variational texture image segmentation models are proposed. In these models, L0 norm smoothing and region based active contour approaches are utilized. Due to the smoothing and edge preserving properties of L0 gradient norm, the first proposed model utilizes L0 gradient norm for smoothing texture and minor details in the image and Mumford Shah data fidelity for segmentation. To get a texture free image, the model is minimized through alternating minimization algorithm and for segmentation, the model is minimized through Euler Lagrange’s equation. For efficient solution, the additive operator splitting method is applied to numerically solve the partial differential equations. As the L1 norm is more robust than L2 norm, therefore, in the next model, instead of the L2 norm, L1 norm is utilized in the data term and L0 gradient norm as a regularization for smoothing texture. For segmentation piecewise Mumford-Shah data term in level set formulation is used. Both the above models depend on the selection of initial contour and also producing staircasing problem. To resolve these issues, a convex variational model is proposed which is the unified form of L0 norm smoothing and convex minimization model. This model is independent of initial contour and overcome the problem of staircasing effect efficiently. Nevertheless, the model still producing problems when segmenting some hard textured images or when the image boundary is unclear and diffused. To overcome these problems, a joint smoothing and segmentation model by using piecewise smooth approximations is proposed. In this model, first, in the fidelity term instead of constant intensity means we approximated the image with piecewise smooth functions. Second, a signed pressure force function is utilized to stop the contours at minor or blurred boundaries and to speed up the process of contour movement. Third, L0 gradient norm is employed to smooth the textured image. In this dissertation, our second goal is to develop a texture image selective segmentation model. As in some cases it is very important to segment a region/part of interest from the whole image. Therefore to achieve this, some geometrical constraint are incorporated in the model. Furthermore, to fulfil our final goal, a multi-phase segmentation model via level set and L0 norm smoothing for texture images is proposed. This model may segment texture, noisy and inhomogeneous images more efficiently as compare to other state of the art models.