Ishtiaq, Abir
PhD
Bahauddin Zakariya University
Multan
KPK
Pakistan
2019
Completed
Zoology
English
http://prr.hec.gov.pk/jspui/bitstream/123456789/12265/1/Abir%20Ishtiaq-PhD%20Zoology-BZU%20Multan-2019%20prr.pdf
2021-02-17 19:49:13
2024-03-24 20:25:49
1676726007464
چلے چلو کہ منزل ابھی نہیں آئی
نحمدہ ونصلی علی رسولہ الکریم امّا بعد فاعوذ بااللہ من الشیطن الرجیم
بسم اللہ الرحمن الرحیم
معزز اسا تذہ کرام اور میرے ہم مکتب شاہینو! آج مجھے جس موضوع پر لب کشائی کا موقع مل رہا ہے وہ ہے:’’چلے چلو کہ منزل ابھی نہیں آئی ‘‘
صدرِذی وقار!
منزل کے حصول کے لیے جدوجہد ہر ذی روح کی خواہش رہی ہے، ہر کس و ناکس اس کے لئے کدوکاوش کرتا ہے، اس کی زندگی کا ہر لمحہ حصولِ منزل کے لئے وقف ہوتا ہے، ہمہ قسم لوگ شبانہ روز اس مقصد کے حصول کی خاطر کوشاں رہتے ہیں ، حصول منزل میں ہر آنے والی رکاوٹوں کو ختم کرنے کے درپے ہوتے ہیں، اور پھر یونہی ان کے لمحاتِ زیست گزرتے رہتے ہیں۔
جنابِ صدر!
حشرات الارض سے لے کر انسان تک ہر ایک اپنی منزل کی طرف گامزن ہے، ہر ایک کی اپنی ایک منزل ہے، مورومگس کی منزل اور ہے، گل لالہ کی منزل اور ہے، جوئے نغمہ خواں کی منزل اور ہے، حر یرو پر نیاں کی منزل اور ہے، زمین پر رینگنے والی مخلوق کی منزل اور ہے، گل لالہ کے گردبھنبھنانے والی شہد کی مکھی کی منزل اور ہے، غلاظت پر چکر لگانے والی مکھی کی منزل اور ہے۔
صدرِ محترم!
گلستان میں عندلیب خوش الحان کی منزل اور ہے، برگد کے درخت پر موجود بوم کی منزل اور ہے، آبادی میں شجر سایہ دار کی منزل اور ہے، ویرانے میں خشک تنے والے درخت کی منزل اور ہے، فضاء میں محو پرواز عقاب وشاہین کی منزل اور ہے ،مُردار کے گرد چکر لگانے والی گدھ کی منزل اور ہے۔
پرواز ہے دونوں کی اسی ایک فضا میں
کرگس کا جہاں اور ہے شاہیں کا جہاں اور
جنابِ صدر!Islāmic Perspective of Inter-Religious Dialogue: A Study of Faith Based Reconciliation
This paper intends to discuss the inter-religious dialogue and the Prophet’s engagement with the ‘Other’. Both dialogue and faith-based reconciliation provide a way to mankind by which the world will become peaceful place to live. In this violence torn world, reconciliation on the basis of faith is needed, so that unity may be created out of diversity. This paper argues that interfaith dialogical theory profits from a deep understanding of moral psychology and social learning theory. The paper highlights that reconciliation belongs to Abrahamic legacy, and also focuses on how Islam established and come up with advanced civilizations characterized by relatively harmonious co-existence between Muslims, Christians and Jews. It is through reconciliation that we regain our humanity. To work for reconciliation is to live and to show others what their humanity is. The paper also shed light on faith-based reconciliation in its Islamic perspective. It is this context the present paper has been drafted. Optical Character Recognition for Printed Urdu Nastaliq Font
Optical Character Recognition (OCR) is one of the most investigated pattern classification problems that has received remarkable research attention for more than half a century. From the simplest systems recognizing isolated digits to end-to-end recognition systems, applications of OCRs vary from postal mail sorting to reading systems in scene images facilitating autonomous navigation or assisting the visually impaired. Despite tremendous research endeavors and availability of commercial recognition engines for many scripts, recognition of cursive scripts still remains an open and challenging research problem mainly due to the complexity of script, segmentation issues and large number of classes to recognize. Among these, Urdu makes the subject of our study. More specifically, this study investigates the recognition of printed Urdu text in Nastaliq style, the most widely employed script for Urdu text that is more complex than the Naskh style of Arabic. This work presents a holistic (segmentation-free) technique that exploits ligatures (partial words) as units of recognition. Urdu has a total of more than 26,000 unique ligatures, many of the ligatures, however, share the same main body (primary ligature) and differ only in the number and position of dots and diacritics (secondary ligatures). We exploit this idea to separately recognize the primary and secondary ligatures and later re-associate the two to recognize the complete ligature. Recognition is carried out using two techniques; the first of these is based on hand-crafted statistical features using hidden Markov models (HMMs). Features extracted using sliding windows are used to train a separate model for each ligature class. Feature sequences of the query ligature are fed to all the models and recognition is carried out through the model that reports the maximum probability. The second technique employs Convolutional Neural Networks (CNNs) to automatically extract useful feature representations from the classes and recognize the ligatures. We investigated the performance of a number of pre-trained networks using transfer learning techniques and trained our own set of networks from scratch as well. Experimental study of the system is carried out on two benchmark datasets of Urdu text, the ‘Urdu Printed Text Images’ (UPTI) database and the ‘Center of Language Engineering’ (CLE) database. A number of experimental scenarios are considered for system evaluation and the realized recognition rates are compared with state-of-the-art recognition systems for printed Urdu text. An interesting aspect of experimental study is the combination of unique ligatures in the two datasets to generate a large set of around 2800 unique primary and secondary ligatures covering a major proportion of the Urdu corpus. The system reports high classification rates (88.10% and 94.78% on CLE and UPTI query ligatures respectively) demonstrating the effectiveness of the proposed recognition techniques which can be adapted for other cursive scripts as well. The findings of this study are expected to be useful for the document recognition community in general and researchers targeting cursive scripts in particular.