کتاب اور صاحبِ کتاب کی نذر
لعل و گوہر سے گِراں تر اُن کی یہ تحریر ہے
ہے یہی تخت شہی ، اُن کی یہی جاگیر ہے
علم سے بڑھ کر کوئی بھی نعمتِ کبریٰ نہیں
علم طاقت، علم دولت، علم ہی شمشیر ہے
اِس میں غوطہ زن تمہیں ہونا ہے میرے دوستو
وقت کا جو خواب ہے اُس کی یہی تعبیر ہے
اختصار و جامعیت کی مرقعّ ہے یہی
بند کوزے میں سمندر ، ان کی ہر تقریر ہے
کس قدر گہری نظر ہے اِن کی سب حالات پر
وقت کے نباض کی منہ بولتی تصویر ہے
چار گوشہ اُن کی شخصیت ہے خود ہی دیکھ لو
اِک مدرس، ایک عالم ہے ،خطیب اور پیر ہے
ظلمتِ شب میں فروزاں نور کا مینار ہیں
سَیف ہے اُن کی زباں ، ہر لفظ میں تاثیر ہے
اک خزینۂ گراں مایہ ہے اُن کی پیشکش
ہر مدرس ، ہر مقرر کے لیے اکسیر ہے
حضرت راشد ؔ کی کاوش مرحبا ، صد مرحبا
اِن کا اِک اِک حرف تائبؔ نعرۂ تکبیر ہے
پروفیسر اکرام تائب
سابق صدر شعبہ (اردو ادبیات)
گورنمنٹ پوسٹ گریجوایٹ کالج عارف والا
Developmental projects are essential ingredients of prosperity and well-being. Every nation has to ensure that her people are living in a perfect and safe sociopolitical environment. However, it varies from region to region and place to place. UK as a country is a big economy which is capable of giving its people the type of security they need. For this purpose, various types of strategies have been emphasized which enable the government to look for the benefit of its people. Open data system is one of these important developments which have been initiated by the UK government to provide huge access to databases. It improves their learning and knowledge, and gives the opportunity to think ‘out of box’. It also enables people to polish their learning skills and take things out of their resources and utilize them fully. Although, there is some compulsion on the use of private data sources, yet it is necessary to know that not all data are confidential. The research looks into the pros and cons of using open data systems and to assess its impacts on the social and political development in UK. The use of open data system is not only beneficial for the people to perform their daily life tasks, it is important to evade corruption and foster great accountability of national institutions. So, there remains feeble chance of witnessing corruption in the society that could cause chaos in the nation. The use of open data systems is important for boosting up innovation and creativity for a developing country like Pakistan. Open data system has been seen playing a big part in establishing a trend of innovative growth pushed by the availability of these resources. The influence and impact of ‘Open Data’ has largely been observed during the recent Coronavirus pandemic (Covid-19) where the government has utilized the data to tackle the disease in Pakistan.
Recognition of online cursive handwriting is difficult and challenging task. This become more cumbersome when it comes to mobile devices where we have small writing area, different writing styles and stroke sequence variation. This research introduces different approaches for recognition of Urdu handwritten characters and word for mobile devices. Comparing all points is resource hungry approach especially for mobile phones. Looking at challenges of mobile phones, Urdu characters are recognized using vectors. It results in fast processing and efficient recognition of Urdu characters consuming lesser resources of the devices. Nevertheless, for complex inputs i.e. online handwritten words proposed technique did not provide good results. Urdu words are compounds of different characters connected with each other. Correct segmentation of online cursive handwriting is difficult to achieve on small writing area. Segmentation free approach is used to recognize Urdu words written on mobile screen. In segmentation free recognition of cursive handwriting, writing rules plays very important role in good and accurate recognition. Looking at shape and location of each character within word, writing rules are designed for Urdu language. A new algorithm is proposed to preprocess the complex input and preserve shape of the actual input. Fuzzy association rules are used to link secondary stroke with their respective primary strokes. Different classifiers such as hidden Markov model (HMM), fuzzy logic, K nearest neighbor (KNN), hybrid HMM fuzzy, hybrid KNN fuzzy and convolutional neural network (CNN) are used for the classification. Statistical tests are applied to find the significance of classifiers results. Experimental results show that by applying proposed preprocessing algorithms and writing rules, recognition rates are impressively enhanced. Vector quantization method provides better results for recognition of online Urdu handwritten characters and hybrid KNN and fuzzy classifier for recognition of ligatures and words in mobile phones.