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Document clustering allows a user to group semantically similar documents. It has been an interesting research area for the past many years and various methods and techniques have been developed. However, the research has primarily been limited to English and other high resource languages. For low-resource languages, such as Urdu, the area of document clustering is open to contributions. This work presents an experimental evaluation of clustering techniques on Urdu tweets. It is a challenging task to semantically cluster tweets due to their very short length. In this paper, various features, including sentence and phrase-level embeddings, TF-IDF features and document embeddings are extracted from tweets and clustering is performed using three different algorithms: K-Means, Bisecting K-Means, and Affinity Propagation algorithms. Furthermore, a comparison is performed with the traditional topic modeling approach. The results indicate that the TF-IDF features combined with the K-means clustering algorithm outperformed the adopted clustering techniques.

The need to protect confidential data stored on personal computers (PCs) or sent to other parties has increased significantly. Therefore, a secure, high-capacity strategy is needed to cover the data contained within media and make it difficult to detect. Due to the limited number of research studies that have achieved these ends through text steganography, we present an innovative approach for hiding secret bits in Arabic text with Unicode Standard seamless. Our method uses the contextual forms of Arabic characters to hide certain secret bits. Extra characters such as Zero-Width Joiners (ZWJ), Kashida, Medium Mathematical Spaces (MMSPs), and Zero-Width Non-Joiners (ZWNJ) are also used to further enhance the method’s capacity without diminishing the data’s security. Our experimental results show that this technique outperforms similar methods with an average improvement in capacity of more than 50%. This technique also has a higher security ratio than the other methods in this study, with the exception of Method 5, and is robust against electronic text modifications such as copying, pasting, and text formatting. Moreover, our algorithm can be widely adopted in related languages, such as Urdu and Farsi, due to its utilization of Unicode characters, which is the encoding standard used in most of the world’s writing systems.

Some scholars of Indology in the 2010s came across one since long hidden manuscript, with a title page in Devanāgarī script dated to 1703, in the Historical Archive of Congregatio de Propaganda Fide in Rome. The manuscript, despite being entitled as Thesaurus Linguæ Indianæ, does not contain a dictionary, but its main part is a complete grammar of the Hindustani language, dated 1704 and written by a Capuchin friar and missionary to India, François Marie de Tours. The finding later led to a rediscovery in Paris of two manuscripts, dated 1703, of the Thesaurus missing in the Rome manuscript by the same author. One of them is supposedly the original and the other one a later copy, produced in 1784. These three manuscripts in Rome and Paris have a common but by scholars in the field forgotten history. Their relation and history will in this article be revealed in detail and contextualized, firstly in a section in which the manuscripts are closely described, secondly in a section about the author as much as is known. A third section will follow the history of the Thesaurus manuscripts in Paris up to the present day.

Purpose The use of social media has increased during the COVID-19 pandemic. Social media platforms provide opportunities to share news, ideas and personal stories. Twitter is used by citizens in Pakistan to respond and comment on emerging news stories and events. However, it is not known whether Twitter played a positive or negative role in spreading updates and preventive messages during the COVID-19 pandemic. The purpose of this study is to analyse content from Twitter during the pandemic. Design/methodology/approach NodeXL was used to retrieve data using the keyword وائرس کورونا (written in Urdu and which translates to Coronavirus). The first data set (Case Study 1) was based on 10,284 Twitter users from the end of March. The second data set (Case Study 2) was based on 10,644 Twitter users from the start of April. The theoretical lens of effective message framing was used to classify the most retweeted content on Twitter. Findings Twitter was used for personal and professional projections and included certain tweets included political motives even during the unfolding health crisis. There appeared to be very few successful attempts to use Twitter as a tool for health awareness and risk communication. The empirical findings indicate that the most retweeted messages were gain-framed and can be classified as personal, informative and political in nature. Originality/value The present study provides insights likely to be of interest to researchers, health organizations, citizens, government and politicians that are interested in making more effective use of social media for the purposes of health promotion. The authors also provide novel insights into the key topics of discussions, websites and hashtags used by Pakistani Twitter users during the COVID-19 pandemic.

Objective To examine the psychometric properties of the Urdu version of the Quality of Life Questionnaire for Physiological Pregnancy (QOL-GRAV). Methods This cross-sectional study was conducted at the Obstetrics, Gynecology department of Sandeman Provincial Hospital, Quetta. The QOL-GRAV was translated into Urdu by using a forward-backward procedure. The test-retest reliability was assessed through Cronbach’s alpha reliability analysis. The validity of the translated questionnaire was constructed by using Exploratory Factor Analysis (EFA) through principal axis factoring extraction and Oblique rotation with Kaiser Normalization. SPSS v 20.0 was used for data analysis with p 0.80. The Kaiser-Meyer-Olkin measure of sampling adequacy for the factor analysis was 0.812. Barlett’s Test of Sphericity was significant (Chi-square = 1032.43; p < 0.05) revealing relationships of the data and suitability of EFA. Three factors explaining the total variance of 65% were extracted whereby loading values for all nine constructs were acceptable (> 0.40). Conclusion The results of this study conclude that the translated version of QOL-GRAV-U is a valid and reliable instrument for the assessment of QoL for pregnant women in regions where Urdu is a prime language of communication. Continuous....

The usage of local languages is being common in social media and news channels. The people share the worthy insights about various topics related to their lives in different languages. A bulk of text in various local languages exists on the Internet that contains invaluable information. The analysis of such type of stuff (local language’s text) will certainly help improve a number of Natural Language Processing (NLP) tasks. The information extracted from local languages can be used to develop various applications to add new milestone in the field of NLP. In this paper, we presented an applied research task, “multiclass sentence classification for Urdu language text at sentence level existing on the social networks, i.e., Twitter, Facebook, and news channels by using N-grams features.” Our dataset consists of more than 1,00000 instances of twelve (12) different types of topics. A famous machine learning classifier Random Forest is used to classify the sentences. It showed 80.15%, 76.88%, and 64.41% accuracy for unigram, bigram, and trigram features, respectively.

The present study aims to translate and adapt the WHO-Five Wellbeing Index (WHO-5) into the Urdu language and then determine its psychometric properties.Male participants (N = 201) between 18 and 4...

Semantic word similarity is a quantitative measure of how much two words are contextually similar. Evaluation of semantic word similarity models requires a benchmark corpus. However, despite the millions of speakers and the large digital text of the Urdu language on the Internet, there is a lack of benchmark corpus for the Cross-lingual Semantic Word Similarity task for the Urdu language. This article reports our efforts in developing such a corpus. The newly developed corpus is based on the SemEval-2017 task 2 English dataset, and it contains 1,945 cross-lingual English–Urdu word pairs. For each of these pairs of words, semantic similarity scores were assigned by 11 native Urdu speakers. In addition to corpus generation, this article also reports the evaluation results of a baseline approach, namely “Translation Plus Monolingual Analysis” for automated identification of semantic similarity between English–Urdu word pairs. The results showed that the path length similarity measure performs better for the Google and Bing translated words. The newly created corpus and evaluation results are freely available online for further research and development.

Increased connectivity has contributed greatly in facilitating rapid access to information and reliable communication. However, the uncontrolled information dissemination has also resulted in the spread of fake news. Fake news might be spread by a group of people or organizations to serve ulterior motives such as political or financial gains or to damage a country’s public image. Given the importance of timely detection of fake news, the research area has intrigued researchers from all over the world. Most of the work for detecting fake news focuses on the English language. However, automated detection of fake news is important irrespective of the language used for spreading false information. Recognizing the importance of boosting research on fake news detection for low resource languages, this work proposes a novel semantically enriched technique to effectively detect fake news in Urdu—a low resource language. A model based on deep contextual semantics learned from the convolutional neural network is proposed. The features learned from the convolutional neural network are combined with other n-gram-based features and are fed to a conventional majority voting ensemble classifier fitted with three base learners: Adaptive Boosting, Gradient Boosting, and Multi-Layer Perceptron. Experiments are performed with different models, and results show that enriching the traditional ensemble learner with deep contextual semantics along with other standard features shows the best results and outperforms the state-of-the-art Urdu fake news detection model.

Stemming is a common word conflation method that perceives stems embedded in the words and decreases them to their stem (root) by conflating all the morphologically related terms into a single term, without doing a complete morphological analysis. This article presents STEMUR, an enhanced stemming algorithm for automatic word conflation for Urdu language. In addition to handling words with prefixes and suffixes, STEMUR also handles words with infixes. Rather than using a totally unsupervised approach, we utilized the linguistic knowledge to develop a collection of patterns for Urdu infixes to enhance the accuracy of the stems and affixes acquired during the training process. Additionally, STEMUR also handles English loan words and can handle words with more than one affix. STEMUR is compared with four existing Urdu stemmers including Assas-Band and the template-based stemmer that are also implemented in this study. Results are processed on two corpora containing 89,437 and 30,907 words separately. Results show clear improvements regarding strength and accuracy of STEMUR. The use of maximum possible infix rules boosted our stemmer's accuracy up to 93.1% and helped us achieve a precision of 98.9%.

During the last two decades, sentiment analysis, also known as opinion mining, has become one of the most explored research areas in Natural Language Processing (NLP) and data mining. Sentiment analysis focuses on the sentiments or opinions of consumers expressed over social media or different web sites. Due to exposure on the Internet, sentiment analysis has attracted vast numbers of researchers over the globe. A large amount of research has been conducted in English, Chinese, and other languages used worldwide. However, Roman Urdu has been neglected despite being the third most used language for communication in the world, covering millions of users around the globe. Although some techniques have been proposed for sentiment analysis in Roman Urdu, these techniques are limited to a specific domain or developed incorrectly due to the unavailability of language resources available for Roman Urdu. Therefore, in this article, we are proposing an unsupervised approach for sentiment analysis in Roman Urdu. First, the proposed model normalizes the text to overcome spelling variations of different words. After normalizing text, we have used Roman Urdu and English opinion lexicons to correctly identify users’ opinions from the text. We have also incorporated negation terms and stemming to assign polarities to each extracted opinion. Furthermore, our model assigns a score to each sentence on the basis of the polarities of extracted opinions and classifies each sentence as positive, negative, or neutral. In order to verify our approach, we have conducted experiments on two publicly available datasets for Roman Urdu and compared our approach with the existing model. Results have demonstrated that our approach outperforms existing models for sentiment analysis tasks in Roman Urdu. Furthermore, our approach does not suffer from domain dependency.

The development of the Hindi/Urdu cinema is intimately connected to the history of artistic performance in India in two important ways. Not only did hereditary music and dance practitioners play key roles in building this cinema, representations of these performers and their practices have been, and continue to be, the subject of Indian film narratives, genres, and tropes. I begin with this history in order to explore the Muslim religio-cultural and artistic inheritance that informs Hindi/Urdu cinema, as well as examine how this heritage has been incorporated into the cinematic narratives that help construct distinct gendered, religious, and national identities. My specific focus is on the figure of the tawa’if dancer, often equated with North Indian culture and nautch dance performance. Analyzing the ways in which traces of the tawa’if appear in two recent films, Dedh Ishqiya and Begum Jaan, I show how this figure is placed in a larger representational regime that sustains nationalist formations of contemporary Indian identity. As I demonstrate, even in the most blatant attempts to define the Indian nation as “Hindu,” the “Muslimness” of the tawa’if—and by extension the cinema she informed in ways both real and representational—is far from relinquished.

Cross-Lingual Text Reuse Detection (CLTRD) has recently attracted the attention of the research community due to a large amount of digital text readily available for reuse in multiple languages through online digital repositories. In addition, efficient machine translation systems are freely and readily available to translate text from one language into another, which makes it quite easy to reuse text across languages, and consequently difficult to detect it. In the literature, the most prominent and widely used approach for CLTRD is Translation plus Monolingual Analysis (T+MA). To detect CLTR for English-Urdu language pair, T+MA has been used with lexical approaches, namely, N-gram Overlap, Longest Common Subsequence, and Greedy String Tiling. This clearly shows that T+MA has not been thoroughly explored for the English-Urdu language pair. To fulfill this gap, this study presents an in-depth and detailed comparison of 26 approaches that are based on T+MA. These approaches include semantic similarity approaches (semantic tagger based approaches, WordNet-based approaches), probabilistic approach (Kullback-Leibler distance approach), monolingual word embedding-based approaches siamese recurrent architecture, and monolingual sentence transformer-based approaches for English-Urdu language pair. The evaluation was carried out using the CLEU benchmark corpus, both for the binary and the ternary classification tasks. Our extensive experimentation shows that our proposed approach that is a combination of 26 approaches obtained an F 1 score of 0.77 and 0.61 for the binary and ternary classification tasks, respectively, and outperformed the previously reported approaches [ 41 ] ( F 1 = 0.73) for the binary and ( F 1 = 0.55) for the ternary classification tasks) on the CLEU corpus.

The authorship identification task aims at identifying the original author of an anonymous text sample from a set of candidate authors. It has several application domains such as digital text forensics and information retrieval. These application domains are not limited to a specific language. However, most of the authorship identification studies are focused on English and limited attention has been paid to Urdu. However, existing Urdu authorship identification solutions drop accuracy as the number of training samples per candidate author reduces and when the number of candidate authors increases. Consequently, these solutions are inapplicable to real-world cases. Moreover, due to the unavailability of reliable POS taggers or sentence segmenters, all existing authorship identification studies on Urdu text are limited to the word n-grams features only. To overcome these limitations, we formulate a stylometric feature space, which is not limited to the word n-grams feature only. Based on this feature space, we use an authorship identification solution that transforms each text sample into a point set, retrieves candidate text samples, and relies on the nearest neighbors classifier to predict the original author of the anonymous text sample. To evaluate our solution, we create a significantly larger corpus than existing studies and conduct several experimental studies that show that our solution can overcome the limitations of existing studies and report an accuracy level of 94.03%, which is higher than all previous authorship identification works.

Word Sense Disambiguation (WSD), the process of automatically identifying the correct meaning of a word used in a given context, is a significant challenge in Natural Language Processing. A range of approaches to the problem has been explored by the research community. The majority of these efforts has focused on a relatively small set of languages, particularly English. Research on WSD for South Asian languages, particularly Urdu, is still in its infancy. In recent years, deep learning methods have proved to be extremely successful for a range of Natural Language Processing tasks. The main aim of this study is to apply, evaluate, and compare a range of deep learning methods approaches to Urdu WSD (both Lexical Sample and All-Words) including Simple Recurrent Neural Networks, Long-Short Term Memory, Gated Recurrent Units, Bidirectional Long-Short Term Memory, and Ensemble Learning. The evaluation was carried out on two benchmark corpora: (1) the ULS-WSD-18 corpus and (2) the UAW-WSD-18 corpus. Results (Accuracy = 63.25% and F1-Measure = 0.49) show that a deep learning approach outperforms previously reported results for the Urdu All-Words WSD task, whereas performance using deep learning approaches (Accuracy = 72.63% and F1-Measure = 0.60) are low in comparison to previously reported for the Urdu Lexical Sample task.

In a short story called ‘Naya Qanun’ or The New Constitution, the Urdu writer Saadat Hassan Manto describes a character called Ustad Mangu’s eager expectation of a new constitution for India.1 Chie...

The article deals with matla‘ (first she‘r – two-line couplet – in a ghazal) of the first ghazal in the Divan by Mirza Asadulla-khan Ghalib (1792–1869) written in Urdu. One of the items usually commented there is the garment made of paper (kāġhażī peirahan). It used to be worn in ancient times by the complainers who appealed to the ruler. The range of complaints in the poetry of Ghalib as well as by other Urdu and Persian poets was wide, however, stable. “Wearing paper clothes”, the petitioner complained about the Almighty, the ill fate, a cruel girl, a lack of understanding of the petitioner’s poetry and the poor remuneration, and finally, about the poet himself, who “dressed” his poems in the paper. Тhese diverse situations form the elements of the literary motif as well as its context and are common in the Persian verses by the predecessors of Ghalib and also himself. Its analysis helps to understand all levels of meaning inherent in one of the most difficult-to-interpret texts by Ghalib.

This essay aims at understanding the development and struggles of a ‘female voice’ within Urdu poetic tradition through the writings of women poets of the Nineteenth century in contrast to the women poets of the twentieth-century feminist movement. The women in traditional Urdu poetry have remained a silent cruel beloved, the image offered is that of a ‘feckless beloved, endowed with heavenly beauty, reigned: fair to face, doe-eyed, dark hair, tall and willowy, a woman who vacillated from indifference, shyness and modesty to wanton cruelty. The essay is an attempt to understand the level of autonomy of the female voice in the poems of women poets through the years. To portray the development of a feminine expression in Urdu poetry the paper will be ranging from the poems of tawaifs (courtesan) of the eighteenth century like Mah Laqa Chanda, their attempts to acquire a place within the patrilineal Urdu literary tradition; the rekhti tradition where men wrote poems in a female voice, to the twentieth century feminist poets like Kishwar Naheed and Fehmida Riaz. The paper is based on Hakim Fasihuddin Ranj’s anthology ‘Baharistan-i-Naz’ which provides a brief yet important introduction on the status of various tawaif poets within the Urdu literary circle; Rahat Azmi’s Halat-i-Mah Laqa, a biographical work on the life and works of Mah Laqa Bai Chanda; and Rukhsana Ahmad’s ‘We Sinful Women’, a compilation of the original and translated works of feminist women poets of twentieth-century Pakistan. Various secondary sources have been used to understand the dynamics behind the writing style of these poets and how similar terms came to be used for portraying completely distinct themes.

In the current study we used the gaze-contingent moving window paradigm to directly compare the second language (L2) English perceptual span of two groups that speak languages with essentially the same lexicon and grammar but crucially with different writing directions (and scripts): Hindi (read left to right) and Urdu (read right to left). This is the first study to directly compare first language (L1) speakers of languages that differ primarily in reading direction in a common L2, English. While Urdu speakers had a slightly faster reading rate, we found no additional differences between Hindi and Urdu speakers when reading L2 English; both groups showed a perceptual span between 9 and 11 characters to the right of the fixation based on saccade length. This suggests little to no influence of L1 reading direction on L2 perceptual span, but rather that L2 perceptual span is influenced by allocation of attention during reading. Our data are in line with research by Leung et al. (2014) finding that L2 speakers have a smaller perceptual span than native speakers (L1 perceptual span is approximately 15 characters to the right of the fixation). This most likely stems from the increased demands associated with reading in a second language, which led to a reduction in the amount of attention that can be allocated outside of the current fixation.

Steganography is the process of hiding data within multimedia communication between parties by embedding the secret data inside a carrier file to be protected during its transmission. This paper addresses the problem of hiding information within the Arabic text as it is currently a challenging research area. Two methods are presented for text steganography: utilizing pseudo-spaces alone and combining them with Kashida (extension character). Experimental results have shown that the proposed algorithms achieved high capacity and security ratio as compared to state-of-the-art steganography methods presented for the Arabic language. The proposed techniques are of great benefit and can be further used for languages similar to Arabic, such as Urdu and Persian, as well as opening the direction of text-stego research for other languages of the world.

Ideologies are constructed and propagated through the subtle use of language. Textbooks are designed deftly to propagate a desired version of social realities to the target reader ship. The present research decodes critically the religious contents present in PTB and OUP primary Urdu textbooks taught at Punjab Pakistan during 2021-2022. The data for the present research has been collected purposively from the chapters containing religious contents in different shad from the selected primary Urdu textbooks. The present research employs an integrated research approach by drawing upon Fairclough (2003, 2012) research models. The levels of analysis include representation, lexicalization, metaphor, rhyme scheme, in/ exclusion and normative critique of language. The findings of the research reveal that representation of religion in the selected data is polarized. The role of economy and class difference contribute a lot in the propagation of religious ideology to middle and elite classes. Besides, it contents that the frequency of occurrence of religious contents is higher in PTB, (book which is 26%) as compared to OUP book where this frequency is 12%. This is how the present study confirms that inclination of middle class towards religion is higher as compared to its counterpart.

Prof. Dr. Muhammad Ishaq Mansoori is a prominent scholar of Arabic and Islamic studies who played a vital role in the promotion of Arabic language and literature in Pakistan. Dr. Mansoori is a great Islamic preacher, good writer, eloquent speaker, expert educationist, an excellent researcher, good mentor and reformer as well. He always strived for the understanding of the holy Quran and the teaching of the Arabic language in Pakistan. He loves Arabic language very much. He edited various textbooks to develop the expertise of the students in Arabic language and understanding of the holy Quran. His sermons, speeches, lectures, articles and scholarly writings published in Urdu language were very easy and simple. In this study, I have viewed his literery services. I adopted the method of description, analytics and historical criticism which covers all the aspects.

Urdu is one of the popular languages across the world as approximately 70 million people speak Urdu in their day-to-day conversations. In general, Muslims prefer to share their opinion or feedback in speech format in the Urdu language. From the literature, it is evident that opinion extraction from naturalistic audio has emerged as a new field of research. In this automatic speech, recognition is carried with keyword spotting approaches on audio, and then opinion score is computed. In this paper, the authors propose a novel framework for the extraction of sentiment from Urdu audio data. Firstly, speech utterances are duly pre-processed, and then short-term features such as Mel-frequency cepstral coefficients, spectral energy, Chroma vector features, perceptual linear prediction (PLP) cepstral coefficients and relative-spectral PLP features are extracted. Five mid-term features, including mean, median, etc., are then derived from those short-term features. In the opinion extraction phase, midterm features of Urdu test utterances are compared with the midterm features of the dictionary of words to cite the opinion as positive, negative, and neutral. The originality of the work involves analyzing the perceptual features to find out the features that contain significant information to extract sentiment in Urdu utterances. In this work, weight mean vector fusion technique is used to fuse the outputs of hidden Markov model and dynamic time warping. In the experiments, 97.1% accuracy is achieved in the sentiment analysis task on the Urdu custom corpus of 600 utterances, which outperforms other state-of-the-art classifiers.

The city of Hyderabad has had a distinct linguistic and political history. It was a multilingual city with Urdu (and Persian) as the court languages under the Asaf Jahi dynasty until 1948, when it ...

The present study deals with all the verified prognostication of the Holy Prophet that He presented in the battle of (Ahzab). Moreover, The Prediction of the victory of Faras and Rome, the prediction of the battlefield of the slain in the war of Badar, similarly, prediction of the victory of Khyber through the hand of Hazrat Ali (R.A), As well as the prediction of a companion being infernal before his death above all the prediction of Hazrat Ibn.e- Abbbas’ ransom and that proved absolutely right one by one. Furthermore, on one side it proved the legitimacy of him while on the other hand righteousness of The Holy Hadiths of the Prophet. In this article, all those prognostication are collected that are narrated thoroughly.

Urdu Short Stories and other poetic and prose genres’ regarding similarities and differences have been discussed in Urdu Fiction Criticism. There are many writers who has given importance to poetry than short story. The declamations of Syed Waqar Azeem, Muhammad Hassan Askari, Qamar Raees, Shams ur Rehman Farooqi, Waris Alvi and Anees Nagi etc. are being discussed in this article. These discussions have major importance in Urdu fiction criticism. This article deals with these discussions objectively and shows the similarities and difference between short story and other literary forms.

Dr. Saleem Akhtar has been a multi-faceted personality of Urdu literature who has made significant contributions in the field of creation of Urdu language and literature. He has served the Urdu Literature in various fields as a critic, correspondent, sketcher, translator, satirist and short story writer, as well as a writer on general psychology. He not only solved centuries-old literary issues in his shortest history book, but also presented a new way to the readers of literature. He presented new ideas in Criticism and create a lot of books in this regard. He also strengthened the field of Iqbaliyat in all over the world. Due to the literary services of Dr. Saleem Akhtar, a permanent tradition of knowledge of Saleem Akhtar has come into existence in which the role of literary magazines is very important. Various Urdu literary journals set up special sections and published articles by eminent critics through which Saleem Akhtar Shinasi was greatly strengthened

An offline handwriting recognition system for Urdu, a language with a user base of 200 Million and written in Nastaleeq script, has been a challenge for the research community. The key problems include recognition of complex ligature shapes and lack of publicly available datasets. This paper addresses both these problems by (i) proposing an end-to-end handwriting recognition system based on a new CNN-RNN architecture with n-gram language modeling, and (ii) presenting a new unconstrained dataset called NUST-UHWR. We compiled the first unconstrained Urdu handwritten data from around 1000 people from diverse background, age and gender population. The text in this dataset is selected carefully from seven different fields to ensure the presence of commonly used words in different domains. The model architecture is capable of incorporating fine-grained features necessary for handwritten text recognition of complex ligature languages. Our method addresses the limitations of existing architectures and provides state-of-the-art performance on Urdu handwritten text. We achieve a minimum character error rate of 5.28% on Urdu handwriting recognition (UHWR) and establish a state-of-the-art. The paper further demonstrates the generalization ability of the proposed model by training on English language and bilingual (Urdu and English) handwritten data.

The Holy Quran is one of the Prove of the Prophethood of the Muhammad S(SAW). It is the greatest miracle of the Holy Prophet (SAW) and as a challenge to the human beings and jins, no one could bring an example like this. One part of this miracle of the Holy Quran is its correlation among the verses and suras. Islamic scholars like; Imame Razi, Allama Zarakshi, Imame Buqa’I, Imame Syuti, Allama Anwar Shah Kashmiri and others say that The Holy Quran is correlated from start to end and it is the prove that it is the word of Allah. In the lexical meaning “correlation” means “being alike” or “to bring into order” while idiomatically it discusses the correlationship among some parts of the Holy Quran with other and its hidden relation. All the verses of the Holy Quran are correlated in one way or the other. This correlation is sometimes very clear but sometimes it is vague. Some of these hidden correlation are named sometimes but many times it cannot be named but they can be understood by having a natural ability and vast study of the Holy Quran. This research article discusses these correlations which can be discussed and named and many of the scholars (specially the exegesits) have discussed in their books which are pointed to here.

PurposeThe present study examines the knowledge, attitude and practice towards the reduction of COVID-19 spread among entrepreneurs of the Federal Urdu University of Arts, Sciences and Technology (FUUAST), Karachi Pakistan.Design/methodology/approachThe authors employed cross-sectional data to infer the results. The data are collected through an online survey questionnaire. To target the respondents; a convenience sampling technique is adopted. In total, 222 usable answers proceed with final results. The structural equation model (SEM) is applied for the data analysis.FindingsThe study outcomes found a significant and positive role of knowledge about COVID-19, attitudes towards a stay at home and practices against COVID-19 in reducing the spread of the pandemic.Practical implicationsThe study provides coherent knowledge about the factors that fight against the pandemic's further spread. The findings would provide the guidelines to policymakers to think about such factors and boost them enormously. Further, the results would contribute to the literature of COVID-19.Originality/valueThis study is original, which empirically confirmed the effect of knowledge about COVID-19, attitudes towards a stay at home and practices against COVID-19 in an academic institute.

As it is believed that all the genres are somehow connected because they all belong to the same entity; man’s imagination which is the birthplace of all the artful & thoughtful ideas ever emerged in human history. This research paper encompasses the whole tradition of travelogues in Urdu literature and figures the elements of fiction in the very genre. The researcher suggests that the travelogue is the mother of all genres and the same core belief is what lays base on the thought-expedition while writing the paper. This is quite evident that travelogue-writer focuses on the facts and the actual details of every journey and utilize them while working on his draft and the same is the very creative strategy for writing fiction, that the fiction writers also get to the actual situations from the society, analyze objectively and then utilize them masterfully for the fictional sequence of the happenings in the story i.e. plot. This research paper helps the readers to envision the creative going on processes regarding fiction writing & travelogue writing both, understand them to an extensive extent and find the similarities which seemingly reflect the other like organic twins. In this regard, it is considered that the genres of travelogue & novel, both explained with meaningful examples and no ambiguity remains.

Elegy started its journey from Arabic Language. Its first creator was Hazrat Adam (AS) at sorrowful murder of his sons Habeel. This article is about the origin and meaning of the word “Elegy”, Elegy in Urdu language its evolution and beginning. In Urdu language, Elegy started from Dakkan.Elegyhad been divided into three types which were conventional, personal and religious or KarbalaiMarsiya.But later on, it became specific for Karba. We can come across personal elegies in Urdu but whenever we mention elegy our attention goes to Karbala. Therefore, in this article Elegy has been discussed in this context. Elegy in differentlanguagesof the world like Greek, Latin, English, French, Italian etc. is also part of this article

Muhammad ManshaYaad was an exclusive Pakistani writer who always tried to uphold the principles rites of honesty and integrity in his literary work. He tried to represent the present age in his fiction. He has interpreted various aspects of life from his specific positive point of view. He always showed his grieves and the pain he felt for the common people. He effortlessly reflected the ethos of Punjabi culture. He has tried to portrait a variety of pictorial representation of simple characters related to real life.

El artículo examina la controversia generada por el poema “Hum Dekhenge”, de Faiẓ Aḥmed Faiẓ, durante las protestas desencadenadas por la aprobación del Citizenship Amendment Act (Enmienda de la Ley de Ciudadanía) y el National Registry of Citizens (Registro Nacional de Ciudadanos) a finales de 2019 en India. Se explican las circunstancias en las que se originó el debate, se proporciona una semblanza del autor del poema y una traducción al español del texto poético, y se exploran diversas interpretaciones. La producción de significado del poema es una articulación compleja entre el texto, los lectores y el contexto sociopolítico. “Hum Dekhenge” es un poema con varios registros lingüísticos, literarios y políticos. Sin duda, su lectura está abierta a múltiples posibilidades.

This article is about urdu fiction writing. The article covers the histological and philosophical back ground of different styles in urdu short. Story writing. It also covers different time periods of popular styles and narrates this writing styles of pioneers of some popular styles. It's also shows the literary work of some popular urdu fiction writers. The article is a brief history of short story and it also tells about future stylistic approaches in the field of urdu short stories. This article narrates significant work of prominent short stories writers and shows the different styles of short stories writers in specified way. Romanticism, realism and symbolism are the major parts of short stories writing. this article cover all this aspects.

One of the striking and significant name of Ghazal poetry during the decade of seventies was Yousaf Hassan. He chose capitalistic mindset and social discrimination in Pakistani society as a permanent subject of his Ghazal. His poetry offers a critique of the materialization of social relations. He aims to posit mutual compassionate empathy and high humanistic values as the characteristic features of an individual. His poetic work Aye Dil Aye Darya comprises of remarkable verses which represent the perception about social as well as class discrimination. The striking feature of this representation is the portrayal of classical as well as traditional metaphors in a progressive context.

Pakistan is an Islamic country and has been established in the name of Islamic ideology but rape and murder of innocent children and ladies, like Zainab presents a very ugly and obnoxious image of this Muslim nation. This research has been done to find the gender issues and feminine injustice in Pakistani press news reports from Critical Discourse Analysis viewpoint in light of teachings of Quran. It is said in the Quranic text: وَمَنۡ يَّعۡمَلۡ مِنَ الصّٰلِحٰتِ مِنۡ ذَكَرٍ اَوۡ اُنۡثٰى وَهُوَ مُؤۡمِنٌ فَاُولٰٓـئِكَ يَدۡخُلُوۡنَ الۡجَـنَّةَ وَلَا يُظۡلَمُوۡنَ نَقِيۡرًا “and whoso doeth good works, whether of male or female, and he (or she) is a believer, such will enter paradise and they will not be wronged the dint in a date- stone”. This research study is done to explain, what Quran says about gender issues and women injustice, using out press statements, images, and columns taking from both in English and Urdu languages newspapers, namely the Dawn and Express. The statements are taken during the week, after happening of brutal episode i.e. from 8 January 2018 to 14 January 2018.Inspiration of this project is created in the background of Zainab’s sexual abuse and gruesome rape, which happened in first week of January 2018. Initially the teachings of Quran, gender issues, feminine injustice and media discourse are explained briefly because injustice with ladies and children have been growing very rapidly since previous two decades in Pakistan. Then the significance of research is highlighted. This research is carried out in the paradigm of qualitative approach. Non probability purposive sampling technique is adopted for sample selection from selected newspapers. Van Dijk CDA model has been implemented for data analysis of the research, but keeping in view the hypothesis of the study the selected points are discussed only. The essential aim of the research is to focus on the pacifier and collusive stance of media, wrapped in the agenda of power which has been explored through Van Dijk CDA model.

Project is completed with Michael Ashton and Kibeom, creators of the HEXACO personality inventory.