پروفیسرڈاکٹر نذیر احمد
(اشتیاق احمد ظلی)
پروفیسر نذیر احمد کے انتقال سے علم و دانش کے میدان میں بالعموم اردو فارسی زبان و ادب کے میدان میں بالخصوص جو خلاء پیدا ہوا ہے اس کا پر ہونا مشکل ہے۔ ان کے علمی اکتسابات اور تحقیقی فتوحات کی فہرست بہت طویل ہے اور اسی طرح ان اعزازات کی بھی جو انہیں تفویض کیے گئے۔ ایران، افغانستان، وسط ایشیا اور جنوبی ایشیا کے علاوہ یورپ و امریکہ کے علمی حلقوں میں ان کے نام اور کام کا بڑا احترام اور اعتراف پایا جاتا تھا۔ ان کی علمی اور تحقیقی دلچسپیوں کا میدان بہت وسیع تھا اور علم و فن کے کتنے ہی تاریک گوشے ان کی فکری کاوشوں سے روشنی میں آئے لیکن تدوین و تحقیق متن اور فرہنگ نویسی ان کے خاص موضوعات تھے جہاں ان کا علم و فن نئی بلندیوں پر نظر آتا ہے۔ دیوان حافظ کے دو قدیم ترین نسخوں کی تحقیق و تدوین کے علاوہ انہوں نے متعدد اہم متون کی بڑی ژرف نگاہی سے تدوین کی اور تحقیق متن کا ایک معیار قائم کیا۔ حافظ پر اپنی تحقیقات کی وجہ سے وہ حافظ شناس کے خطاب سے موسوم ہوئے۔ مصوری، خطاطی اور موسیقی جیسے مختلف النوع موضوعات پر ان کا مطالعہ بہت وسیع تھا اور ان موضوعات پر انہوں نے بڑا وقیع تحقیقی سرمایہ یادگار چھوڑا ہے۔ ان کی شخصیت میں اتنے متنوع اور گونا گوں اوصاف اور کمالات جمع ہوگئے تھے کہ انہیں دیکھ کر علماء سلف کی یاد تازہ ہوجاتی تھی۔ علم و فضل اور شہرت و ناموری کے اتنے اونچے مرتبہ پر فائز ہونے کے باوجود ان کے مزاج میں بڑی سادگی، انکسار اور تواضع تھی۔ اپنے خوردوں سے بھی بڑی خندہ پیشانی اور تواضع سے پیش آتے۔ ان کے مقام و مرتبہ کا ادراک صرف اس وقت ہوتا تھا...
As well as per Shariah, it is admissible and some of the time even mandatory to save the devotees from the activities that might lead them towards the prohibited exercises. Consequently, the decision of denial from these kinds of exercises is called Sadd-e-Zaree'a. This is the guideline derived from the Quran and Sunnah. As Almighty Allah prohibited the devotees to say 'Raina' because this word was utilized by Jews purposely in an off-base way with underhanded aims, while, Muslims introduced their solicitations by this equivalent word in the most elevated court of The Holy Prophet (harmony and gifts arrive) for looking for effortlessness and unwinding in their concerned issues. As in Quran: O People who Believe, don't tell (the Prophet Mohammed-harmony and gifts arrive), "Raina (Be accommodating towards us)" however say, "Unzurna (Look leniently upon us)", and listen mindfully in any case. [Baqarah 2:104]. (To disregard the Holy Prophet - harmony and endowments arrive - is impiety.) Ibn Hazm in his famous book Al-Aḥkām Fī ūṣūl Al-Aḥkām has objected to the mentioned verse from which jurists have taken the argument of Sadd-e-Zaree'a. Because the Zahiri school of thought is based on the appearance of the text (Quran o Hadees). This is why Ibn Hazm Zahiri denies it (the source of Shariah), and proves that accepting the source of Shariah is an increase in religion which is in itself illegitimate as well as the opposition of the Prophet (peace and blessings of Allah be upon him). There is also the addition of items by their thoughts in Shariah. In the above article, an analytical study of the objections of Allama Ibn Hazm will be presented, explaining the sources and the arguments as to whether or not their source is Shariah.
Biometric recognition systems are considered to be one of the most secured means of authentication. In this context several biometrics have been proposed but the view based biometrics such as face, iris etc remain the most natural choice. In the paradigm of face recognition, it is generally assumed that major information contents lie in the lower frequency region of an image and therefore little effort has been made in sys tematic exploration of the detail images. Although some wrapper-based approaches have been proposed in the literature, they are primarily based on experimental eval uation of a specific classifier on various subbands. Therefore there is a dire need of a framework for automatic selection of the most significant subbands based on the underlying statistics of the data. In this thesis, the problem of identifying the most dis criminant subbands based on information theoretic measures is addressed. Essentially the face images are transformed into textures using the linear binary pattern (LBP) ap proach, these texturized-faces undergo the wavelet packet decomposition resulting in several subband images. We propose to use the energy features to effectively represent these subband images. The underlying statistical patterns of the data are harnessed in form of information-theoretic metrics to select the most discriminant subbands. The proposed algorithms are extensively evaluated on several standard databases and are shown to always pick the most significant subbands resulting in better performance. The proposed algorithms are entirely generic and do not depend on the validation re sults for specific classifiers. Noting that localized features are often more useful than theholisticapproaches, wehavealsotargetedtheproblemofirisrecognitionproposing the concept of class-specific dictionaries. Essentially, the query image is represented as a linear combination of training images from each class. The well-conditioned inverse problem is solved using least squares regression and the decision is ruled in favor of the class with the most precise estimation. An enhanced modular approach is further proposed to counter noise due to imperfect segmentation of the iris region. As such iris images are partitioned and individual decisions of all sectors are fused using an efficient fusion algorithm. The proposed algorithm is compared to the state-of-the-art Sparse Representation Classification (SRC) with Bayesian fusion for multiple sectors. The proposed approach has shown to comprehensively outperform the SRC algorithm on standard databases. Complexity analysis of the proposed algorithm shows decisive superiority of the proposed approach.