مولانا حافظ محمد تقی امینی
ڈاک کا نظام اس قدر اتبر ہے کہ مہینوں سے دارالمصنفین میں اردو کا کوئی اخبار نہیں آرہا ہے، اس لیے ضروری اور اہم خبروں کا بھی علم نہیں ہوتا، پروفیسر مختارالدین احمد صاحب کو اﷲ تعالیٰ جزائے خیر دے جن کے گرامی نامہ سے دارالمصنفین کے ایک مخلص کرم فرما مولانا حافظ محمد تقی امینی کی حسرتناک وفات کی اطلاع تاخیر سے ملی۔
مولانائے مرحوم مسلمانوں کے قدیم و جدید دونوں طبقوں میں مقبول اور ہر دلعزیز تھے، علی گڑھ مسلم یونیورسٹی میں انھوں نے بڑی نیک نامی اور عزت حاصل کی، وہ ایک عالم دین اور اسلامیات کے فاضل و محقق اور مصنف کی حیثیت سے پورے ملک میں مشہور تھے، دینی علوم میں بلند پائیگی کے ساتھ ساتھ وہ اخلاص، عمل، ﷲیت، بے نفسی اور زہد و اتقا میں بھی ممتاز تھے، ان کی وفات سے علمی و دینی حلقوں میں جو خلا پیدا ہوا ہے اس کا پر ہونا مشکل ہے۔
۱۹۵۰ء میں میں عربی کا متبدی تھا اور اسی زمانے سے معارف کی ورق گردانی کرتا تھا، اس کے جن مضمون نگاروں کے نام لوح دل پر ثبت ہوگئے تھے ان میں مولانا کا نام بھی تھا کیونکہ تھوڑے تھوڑے وقفوں کے بعد برابر ان کے مضامین معارف میں شائع ہوتے رہتے تھے، سنہ تو یاد نہیں لیکن ان سے پہلی ملاقات دارالمصنفین میں اس وقت ہوئی جب وہ علی گڑھ مسلم یونیورسٹی کے شعبۂ دینیات کے ناظم ہوچکے تھے اور گرمیوں میں مطالعہ و کتب بینی کے لیے اعظم گڑھ تشریف لائے تھے۔
وہ مولانا شاہ معین الدین احمد ندوی مرحوم سابق ناظم دارالمصنفین کے مہمان تھے جن کے ساتھ ہی میرا کھانا پینا بھی ہوتا تھا، شاہ صاحب نے مولانا کا پلنگ میرے کمرے میں لگوا دیا تھا اس طرح تقریباً ایک ماہ تک...
Allah Almighty, with his power, created the sky, earth and whole universe and provided all the necessities. Therefore, the work of preaching Islam is conferred upon the Ummah of Holy Prophet (P.B.U.H). There are the people who had been taught the teachings of Islam directly by Holy Prophet and they preached Islam in the same way as they were taught. They practiced all the teachings in their lives. Sahaba R.A, for preaching Islam, went to the east, west, north, south, Hind, Sindh and the corners of the world. As a result of their efforts, almost half of the world got the message of Islam. Tabaeen consisted of many people, in the light of Quran and Sunnah, conveyed the message of Islam throughout the world. In the same way, another group of people named Tab Tabaeen became prepared to spread the universal message of Islam. They didn't ignore any sacrifice to uplift the spirit of Islam. With their struggle, many great people like saints, jurist, reader and interpreter of Quran and Hadith born. These people tried their best to convey the message of Islam through written and spoken discourse. Religious books and places were introduced. That process of education, after many years, is still continuing. Presently, many religious places are constructed to preach spiritual guidance in which many great scholars and saints are engaged. History is witness that opponents went to extent possible level to aloof Muslims from teaching, preaching and guiding of lslam. Not only were this but the Muslims intended to end also. In these trials and tribulations, saints took responsibility on their shoulders and continued their struggle on the directed path of oneness, Prophet hood, Ahle Bait and Sahabas against the evil forces. Among such great Family of Pir Pagara is one whose line is continuing in Hind and Sindh. Insha Allah (If God wills) it'll continue till the last day. There is his great religious and social contribution. To convey, his valiant services towards people, research on this personality is dire need of the hour. In history, this research will be advantageous for the researchers to come.
Images and graphics are among the most important media formats for human communication and they provide a rich amount of information for people to understand the world. With the rapid development of digital imaging techniques and Internet, more and more images are available to public. Consequently, there is an increasingly high demand for effective and efficient image indexing and retrieval methods. However with the widely spread digital imaging devices, textual annotation of images be- comes impractical and inefficient for image representation and retrieval. To diminish the reliance on the textual annotations and associated meta- data for image search, the content based image retrieval (CBIR) has be- come one of the most popular topics in the field of computer vision and pattern recognition. In CBIR, the image representations are generated through the visual clues like color, texture, or shape of objects; and cer- tain machine learning algorithms are applied to understand the image semantics for meaningful image retrieval. However, despite the great deal of research work, the image retrieval performance of the CBIR sys- tems is not satisfactory due to the existent semantic gap between the low-level image representations and high-level visual concepts. To bridge this gap to some extent, three major issues in the active field of CBIR are investigated in this thesis, that are: consistency enhancement during the semantic association, improvement in the relevance feedback (RF) mechanism, and generation of a stable semantic classifier. Consistency enhancement in semantic association process, addresses the two main reasons, due to which the conventional CBIR systems are not able to produce the effective retrieval results. These are: the lack of output verification and neighborhood similarity avoidance. Due to these problems the image response is very inconsistent and the target output contains far more wrong results as compared to the right results. In this thesis, we concentrate these issues by applying the Neural Networks over the bag of images, and exploring the query’s semantic association space. In this regard semantic response of the top query neighbors is also taken into the account. The potential image retrieval is strongly dependent on the efficacy of the image representations. Therefore the deep texture analysis is performed through the best basis of the wavelet packets and Gabor filter to explore the representations which may serve as the most effective basis for automatic image retrieval. The Relevance feedback (RF) in CBIR, specifically focuses on the cus- tomization of the search results to the user’s query preferences based on the several feedback rounds. These systems can easily be mislead by theover-sensitivity in the subjective labeling. Another problem that usu- ally occur is the imbalanced class distribution that makes the classifier learning a real challenge. The amalgamation of both is a big reason for the user frustration, and hence make the system of no practical use. We overcome both of these issues through Genetic Algorithms, and demon- strated the positive performance impacts by SVM classifier. Extending the ideas for imbalance distribution in binary classification to multi-category environment leads in the form of a stable semantic classi- fier. The semantic association becomes even more challenging when there are many categories enrolled. The reason is that: the positive training samples for a particular class are naturally far less then the training samples from many other classes. Weak classifiers like SVM and Neural networks are not able to perform well in these circumstances. Therefore the most effective solution lies in the exploitation of the combined basis function for these week candidates. The Genetic classifier comity learn- ing (GCCL) is tuned for overcoming the limitations like classification biasness in multi-category environment, incompatible parameter estima- tion, and overfitting due to the high dimensional nature of the feature vectors compare to the training sets. The qualitative and quantitative analysis shows that the proposed method outperform many state-of-the- art methods.