آصف علی
افسوس ہے کہ اس مہینہ کے شروع میں ہماری قومی و ملی جماعت کی دو ممتاز شخصیتیں ہم سے جدا ہوگئیں یعنی آصف علی مرحوم اور شفیق الرحمن مرحوم قدوائی نے انتقال کیا، یہ دونوں پرانے قومی کا رکن تھے، ملک و وطن کی انھوں نے بڑی خدمات انجام دیں اور اس کے لئے قید و بند کی مصیبتیں جھیلیں، ہندوستان کی آزادی کی جدوجہد میں ان کا نمایاں حصہ تھا، آصف علی صاحب مرحوم تو پرانے آدمی اور مشہور و ممتاز شخصیت رکھتے تھے، سیاسی ز ندگی سے پہلے بھی وہ ایک اچھے بیرسٹر تھے، اور سیاست کے میدان میں بھی ان کو نمایاں مقام حاصل تھا، اور ہندوستان کے بڑے لیڈروں میں ان کا شمار تھا، ہندوستان کی آزادی کے بعد وہ مرکزی حکومت کی وزارت، اڑیسہ کی گورنری، امریکہ اور سوئیزرلینڈ کی سفارت جیسے بڑے بڑے عہدوں پر ممتاز رہے، اور سو ئیزرلینڈ میں ہی ان کا انتقال ہوا، علمی حیثیت سے بھی وہ بڑے لائق اور ذہین وذکی تھے، اردو کے بھی ادیب تھے اور انگریزی و اردو دونوں میں ان کی تصانیف ہیں، انتقال کے وقت ۶۴، ۶۵ سال کی عمر تھی، ان کی موت سے ایک ایسی جگہ خالی ہوگئی جس کا موجودہ حالات میں پر ہونا مشکل ہے۔ (شاہ معین الدین ندوی، اپریل ۱۹۵۳ء)
The growth of the Sharia banking system in Indonesia is considered a measure of Sharia's economic success. The Indonesian Sharia Banking Supervision is responsible for regulating sharia banking activities. It is important to note that this information is from a regulatory point of view. The regulation and supervision of sharia banking activities are based on amendments to Act No. 3 of 2004 on the Bank of Indonesia, No. 23 of 1999, and Law No. 21 of 2008. After the passing of OJK Act No. 21 in 2011, Indonesian banks were granted the authority to oversee Sharia banks, which were then transferred to the JSC. The Financial Services Authority was formed due to concerns from various parties about the supervisory function of Indonesian banks in regulating Sharia banking. The JSC does not directly monitor all activities of Sharia institutions, but rather ensures that certain aspects are overseen by other institutions, such as the DPS (Dewan Pengawas Syariah). The DPS is responsible for overseeing Sharia Financial Institutions, and is registered based on the approval of the National Sharia Council (DSN). The objective of the OJK is to meet and protect the needs and interests of the public, create a stable and sustainable financial system, and implement a financial system based on the principles of good governance, which include accountability, transparency, and independence.
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.