مولانا مفتی محمود احمد نانوتوی
افسوس! گزشتہ مہینہ ہمارے شبستان دارالعلوم دیوبند کے دو اور روشن چراغ بجھ گئے۔ مولانا مفتی محمود احمد صاحب نانوتوی ناتوتہ کے ایک اعلیٰ اور شریف خاندان کے فردِ فرید تھے۔ تعلیم دیوبند میں پائی تھی، اولاً حضرت شیخ الہند اور پھر حضرت الاستاذ مولانا محمد انورشاہ الکشمیری سے خاص استفادہ کیااوران سے تلمذ خصوصی کاتعلق رکھتے تھے ۔علم وفن کی پختہ استعداد وزہد وورع اوراخلاق فاضلہ، یہ تینوں اوصاف بزرگان دیوبند کے امتیازی کمالات تھے۔ مفتی صاحب بھی ان کے جامع تھے ۔لیکن انھوں نے فقہ اورحدیث کواپنا خاص فن بنالیا تھااور ان میں ان کی نظر بڑی دقیق اور غامض تھی۔ایک عرصہ سے اجین میں قیام پذیر تھے۔وہاں کی مسلم اورغیرمسلم آبادی کوانھوں نے اپنے علم وفضل اور کردار سے کس درجہ عقیدت مند بنالیا تھااس کااندازہ اس سے ہوگا کہ جب ان کا جنازہ اٹھاہے تو تنگیِ وقت کے باوجود کم وبیش پندرہ ہزار آدمی اس کے جلوس میں تھے اور ان میں جن سنگھی بھی تھے ۔ دارالعلوم کی مجلس شوریٰ کے دیرینہ رکن تھے اور اس کی ہر ممکن خدمت کواپنا فرض سمجھتے تھے۔ حضرت شاہ صاحب سے عقیدت کیا ان کے نام کے عاشق تھے۔مجلس میں جب کبھی حضرت الاستاذ کاذکر چھڑ جاتا تو دوسروں کی باتیں بڑی توجہ اوردل چسپی سے سنتے اور پھر جب خود بولنا شروع کرتے توعالم ہی عجیب ہوتا جس کو سن کردل ودماغ دونوں روشن ہوجاتے تھے۔ رحمہ اﷲ رحمۃً واسعۃ۔
[فروری ۱۹۶۹ء]
This descriptive quantitative research paper attempts to explore how women employees at one of the public universities in province of Sindh perceive their profession and societal attitudes including those of colleagues, family and neighbours towards these professional women and their profession. The target participants of this study were academic and non-academic women who had minimum 5 years work experience. Through random sampling technique 100 women (50 from each category) were selected for taking part in survey questionnaire. Findings suggest a positive shift in societal attitude towards professional women in general and working in universities in particular. Interestingly, non-academic respondents perceived societal attitude more positive and supportive than those of academic.
The whole class of evolutionary computing algorithms is inspired by the process of evolution in nature. Compared to the traditional optimization algorithms, a few striking features of these algorithms include their ability to address non-differentiable cost functions, robustness to the dynamically changing environment, and implementation on parallel machines. However, it was not until one and half decade ago, when these algorithms attracted researchers and got acknowledgement in terms of their application to the real world problems. The main reason behind this increased interest of the researchers owes to the ever increasing computing power. As a result evolutionary computing algorithms have been widely investigated and successfully applied for a number of problems belonging to diverse areas. In this dissertation the standard binary particle swarm optimization (PSO) and its soft version, namely soft PSO (SPSO) have been applied to four different problems of digital communication. Due to the exponentially growing computational complexity with the number of users in optimum maximum likelihood detector (OMLD), suboptimum techniques have received significant attention. We have proposed the SPSO for the multiuser detection (MUD) in synchronous as well as asynchronous multicarrier code division multiple access (MC- CDMA) systems. The performance of SPSO based MUD has been investigated to be near optimum, while its computational complexity is far less than OMLD. Particle swarm optimization (PSO) aided with radial basis functions (RBF) has been suggested to carry out multiuser detection (MUD) for synchronous direct sequence code division multiple access (DS-CDMA) systems. The MUD problem has been taken as a pattern classification problem and radial basis functions have been used due to their excellent performance for pattern classification. The two variants of PSO have also been used in a joint manner for the task of the channel and data estimation based on the maximum likelihood principle. The PSO algorithm works at two different levels. At the upper level the continuous PSO estimates the channel, while at the lower level, the soft PSO detects the data. The simulation results have proved to be better than that of joint Genetic algorithm and Viterbi algorithm (GAVA) approach.