حامد نعمانی مرحوم
مولانا شبلی نعمانی ؒ کی ایک ہی جسمانی یادگار باقی رہ گئی تھی وہ بھی مٹ گئی، یعنی ان کے اکلوتے صاحبزادہ حامد نعمانی صاحب نے ۶۲؍ برس کی عمر میں ۲؍ ربیع الاول ۱۳۶۱ھ مطابق ۲۰؍ مارچ ۱۹۴۲ء کی شب کو جونپور میں دفعتہ وفات پائی، وہ کئی برس سے مرض قلب میں گرفتار تھے، علاجوں کے سہارے سے چلتے پھرتے تھے، مگر اندر سے کھوکھلے ہوچکے تھے، ۱۹؍ مارچ کو وہ ایک ضرورت سے جونپور گئے تھے، شام کو پہنچے، اپنا کام کیا، رات کو ۳ بجے کے قریب درد دل کا دورہ ہوا،ان کے میزبان دوست ان کے کراہنے کی آواز سن کر ان کے پاس آئے، مرحوم نے کہا کہ مجھے ذرا سہارا دے کر بٹھا دو، انہوں نے اپنے سینے کے سہارے سے بٹھا دیا، اسی کے ساتھ مرحوم نے ان کو السلام علیکم کہا، اور آخری سانس لے کر نامعلوم سفر کی منزل پر روانہ ہوگئے، انا ﷲ و انا الیہ راجعون، ۲۰ کی صبح کو لاش کار سے اعظم گڑھ آئی، اور شبلی منزل میں باپ کے پہلو میں بیٹے کو ہمیشہ کے لیے سلا دیا گیا۔
مرحوم بڑے توانا و تندرست، قوی ہیکل، بلند و بالا، اور علی گڑھ کالج کے مشہور کھلاڑیوں میں تھے، گھوڑے کی سواری اور پولو میں بھی ممتاز تھے، تحصیلداری کے عہدہ پر فائز ہوکر پنشن پائی پھر ریاست منجھولی میں منیجر ہوئے، مگر صحت کی خرابی کے سبب سے مستعفی ہوگئے، پابند صوم و صلوٰۃ، نیک دل اور بہت رحیم المزاج تھے، اپنی ذاتی زندگی میں گو وہ بہت قانع اور منتظم تھے مگر اس طرح سے جو بچتا تھا، اس کو ہمیشہ فیاضی کے ساتھ نیک کاموں میں لگادیا کرتے تھے، ۱۹۲۷ء میں حج بھی کیا تھا ، زکوۃ کا پورا حساب رکھتے تھے، اﷲ تعالیٰ ان پر رحمت...
Swat valley with reference to its history is a famous region. Many civilizations originated in this land and that’s where they ended. Buddhism had a golden age in swat. Hinduism had also been in this land for some time. Artifacts from Greece and the Kushan period are also found here. The artifacts and traces of all these civilizations still exist in swat today. Similar artifacts have been discovered by the efforts of experts however, the gravity of the earth chest is much greater. Swat archeology is threatened by human population and some religious misunderstanding. Protecting Non-Muslim places of worship and respecting their emotions is a part of Islamic teachings. This paper describes the sharī‛ah rules of archeology and also different types of archeological sites like buildings, worship places and mentioning the orders related to idols etc.
Time is deemed as paramount aspect in Information Retrieval (IR) and it pro foundly influence the interpretation as well as the users intention and expectation. The temporal patterns in a document or collection of documents plays a central role in the effectiveness of IR systems. The accurate discernment plays an immense role in persuading the time-based intention of a user. There exists a plethora of documents on the web wherein most on them contain the divergent temporal pat terns. Assimilation of these temporal patterns in IR is referred to as Temporal Information Retrieval (TIR). The comprehension of TIR systems is requisite to address the temporal intention of a user in an efficient manner. For time specific queries (i.e. query for an event), the relevant document must relate to the time period of the event. To attenuate the problem, the IR systems must: determine whether the document is temporal specific (i.e. focusing on single time period) and determine the focus time (to which the document content refers) of the documents. This thesis exploits the temporal features of the news documents to improve the retrieval effectiveness of IR systems.As best to our knowledge, this thesis is the pioneer study that focuses on the problem of temporal specificity in news docu ments. This thesis defines and evaluate novel approaches to determine the tem poral specificity in news documents. Thereafter, these approaches are utilized to classify news documents into three novel temporal classes. Furthermore, the study also considers 24 implicit temporal features of news documents to classify in to; a) High Temporal Specificity (HTS), b) Medium Temporal Specificity (MTS), and c) Low Temporal Specificity (LTS) classes. For such classification, Rule-based and Temporal Specificity Score (TSS) based classification approaches are proposed. In the former approach, news documents are classified using a proposed set of rules that are based on temporal features. The later approach classifies news documents based on a TSS score using the temporal features. The results of the proposed approaches are compared with four Machine Learning classification algorithms: Bayes Net, Support Vector Machine (SVM),Random Forest and Decision Tree. x The outcomes of the study indicate that the proposed rule-based classifier outper forms the four algorithms by achieving 82% accuracy, whereas TSS classification achieves 77% accuracy. In addition, to determine the focus time of news documents, the thesis contem plates the temporal nature of news documents. The type and structure of doc uments influence the performance of focus time detection methods. This thesis propose different splitting methods to split the news document into three logical sections by scrutinizing the inverted pyramid news paradigm. These methods in clude: the Paragraph based Method (PBM), the Words Based Method (WBM), the Sentence Based Method (SBM), and the Semantic Based Method (SeBM). Temporal expressions in each section are assigned weights using a linear regres sion model. Finally, a scoring function is used to calculate the temporal score for each time expression appearing in the document. Afterwards, these temporal expressions are ranked on the basis of their temporal score, where the most suit able expression appears on top. Two evaluation measures are used to evaluate the performance of proposed framework, a) precision score (P@1, P@2) and average error years. Precision score at position 1 (P@1) and position 2 (P@2) represent the correct estimation of focus at the top 2 positions in the ranked list of focus time whereas, average error year is the distance between the estimated year and the actual focus year of news document. The effectiveness of proposed method is evaluated on a diverse dataset of news related to popular events; the results re vealed that the proposed splitting methods achieved an average error of less than 5.6 years, whereas the SeBM achieved a high precision score of 0.35 and 0.77 at positions 1 and 2 respectively. The overall findings presented in this thesis demonstrate that the valuable tempo ral insights of documents can be used to enhance the performance of IR systems. The time aware information retrieval systems can adopt these findings to satisfy the user expectation for temporal queries.