خلع فسخ نکاح ہے یا طلاق فقہائے کرام کی آراء کا تجزیاتی مطالعہ Whether Khula is Dissolution of Marriage or Divorce Critical Analysis of the Views of Islamic Jurists

Islam is an entire way of life. It illuminates every facet of daily existence. There is no problem for which Islam has not provided a remedy. Every aspect of beliefs and ethics, including human affairs, has also been examined. Islam is the only religion on earth that can be compared the height of Western culture and civilization. People have become its slavish disciples in the most literal sense. To stay up with the rest of the world, they are creating new interpretations of Islam for this reason. Accepted wisdom is a benefit, but only within the bounds of Sharia. Otherwise, it is Shaytan's legacy. ۔(شیطان) One of the most significant and crucial stages in a person's life is the nikah. It is expressly covered in the Qur'an and Hadith. It is created necessary for sustaining human existence. It is referred to as the culmination of human life and one of the Prophet's (ﷺ) required Sunnas. However, one of the most despised actions is the dissolution of a marriage. Islam, however, differs from other faiths. It contains the entire procedure/laws for dissolving a marriage. The appropriate discussion of Talaq and Khula is illustrated by the jurists' use of Estihsan and Qayas. Recent years have seen various crises and a collapse in Pakistani society. Smear and family system disturbance are the main issues among them. "Nikkah" is the fundamental element of a family system; in reality, a family system is based on Nikkah. If this Nikkah is intact, the entire family system is stable; nevertheless, if this Nikkah is broken, not only is the family system traumatised, but the entire society begins to suffer. The summary of this thesis explains that the Islamic Ideological Council's recommendations have been reviewed in light of the non-Sharia practises of the judicial authorities in relation to Khula and judicial powers related to Khula, as well as an analytical study of the remarks and opinions of commentators and jurists, including future jurists, regarding Khula. Key Words: Khul‘a, Judicial Khul‘a, Tansīkh e Nikaḥ, Divorce, ‘Īddat.

Generic Urdu Nlp Framework for Urdu Text Analysis: Hybridization of Heuristics and Machine Learning Techniques

The internet was initially designed to present information to users in English. However, with the passage of time and the development of standard web technologies such as browsers, programming languages, libraries, frameworks, databases, front and back-ends, protocols, APIs, and data formats, the internet became a multilingual source of information. In the last few years, the natural language processing (NLP) research community has observed a rapid growth in online multilingual contents. Thus, the NLP community maims to explore monolingual and cross-lingual information retrieval (IR) tasks. Digital online content in Urdu is also currently increasing at a rapid pace. Urdu, the national language of Pakistan and the most widely spoken and understandable language of Indian sub-continent, is considered a low-resources language (Mukund, Srihari, & Peterson, 2010). Part of speech (POS) tagging and named entity recognition (NER) are considered the most basic NLP tasks. Investigation of these two tasks in Urdu is very hard. POS tagging, the assignment of syntactic categories for words in running text is significant to natural language processing as a preliminary task in applications such as speech processing, information extraction, and others. Named entity recognition (NER) corresponds to the identification and classification of all proper nouns in texts, and predefined categories, such as persons, locations, organizations, expressions of times, quantities and monetary values, etc. it is considered as a sub-task and/or sub-problem in information extraction (IE) and machine translation. NER is one of the hardest task in Urdu language processing. Previously majority Urdu NER systems are based on machine learning (ML) models. However, the ML model needs sufficiently large annotated corpora for better performance(Das, Ganguly, & Garain, 2017). Urdu is termed as a scared resource language in which sufficiently large annotated corpus for ML models’ evaluation is not available. Therefore, the adoption of semi-supervised approach which is largely dependent on usage of the huge amount of unlabeled data is a feasible solution. In this thesis, we propose a generic Urdu NLP framework for Urdu text analysis based on machine learning (ML) and deep learning approaches. Initially, we addressed POS challenges by developing a novel tagging approach using the linear-chain conditional random fields (CRF). We employed a strong, stable, balanced language-independent and language dependent feature set for Urdu POS task and used the method of context words window. Our approach was evaluated against a support vector machine (SVM) technique for Urdu POS - considered Abstract WAHAB KHAN Reg: No. 72-FBAS/PHDCS/S12 vi as the state of the art - on two benchmark datasets. The results show our CRF approach to improving upon the F-measure of prior attempts by 8.3 to 8.5%. Secondly, we adopted deep recurrent neural network (DRNN) learning algorithms with various model structures and word embedding as a feature for the task of Urdu named entity recognition and classification. These DRNN models include long short-term memory (LSTM) forward recurrent neural network (RNN), LSTM bi-directional RNN, backpropagation through time (BPTT) forward RNN and BPTT bi-directional RNN. We consider language-dependent features such as part of speech (POS) tags as well as language independent features such as N-grams. Our results show that the proposed DRNN-based approach outperforms existing work that employ CRF based approaches. Our work is the first to use DRNN architecture and word embedding as a feature for Urdu NER task and improves upon prior attempts by 9.5% in the case of maximum margin.