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در عدالتِ علے

در عدالت علے

                ’’در عدالت علے‘‘علی اکبر ناطق کی مناقب اہل بیت کا مجموعہ ہے۔مولا کی طرف سے خاص عطا کیا ہوا۔ ان کے کلام نے مولا علی کے قصائد آئمہ طاہرین کے حضور نذرانے کے طور پر کلام پیش کیا ہے۔قاری جب پڑھتا ہے تو بے اختیار پکار اٹھتا ہے کہ مصنف نے اس کا حق ادا کردیا ہے۔انہوں نے اس میں تاریخِ حق کو بیان کیا ہے کہ کس طرح  تاریخِ حق کو منقبت میں سمو دیا گیاہے۔در عدالت علے عکس پبلی کیشنز نے 2020ء میں شائع کی۔اس کا انتساب سید اظہر علی عابد کے نام ہے۔اس کتاب نے مذہبی اور ادبی حلقوں میں یکساں طور پر ارتعاش پیداکیا ہے۔ انہوں نے اس میں ایک نظم ’’یاعلی میں گداؤں کی بستی کا ساکن‘‘کے عنوان سے لکھی ہے۔جس سے ان کا علی سے عشق کی انتہا کا ثبوت ملتا ہے۔یہ نظم انسان کے دل ودماغ کی پاکیزگی اور اس کے کردار کو بلندی کی طرف مائل کرتی ہے۔وہ بتاتے ہیں کہ ایک دن وہ اسلام آباد میں تھے۔ظہور امام کے دن تھے۔وہ بتاتے ہیں کہ سید منظر نقوی کے ساتھ جامعہ صادق جی نائن اسلام آباد میں مجلس سننے کے واسطے پہنچا۔سید اظہر نے جیسے ہی مجھے قریب پایا تو مجھے سلام پڑھنے کیلئے کہہ دیا۔وہ کہتے ہیں کہ ان کے ہاتھ پاؤں پھول گئے کیونکہ کلام پاس نہیں تھااور لکھا ہوا کچھ یاد نہیں تھا۔خیر قدم اٹھتے چلے گئے اورایک نظم جو اسلامک کو ذہن میں رکھ کر لکھی تھی اسی کے شعر پڑھنے لگے ناطق بتاتے ہیں کہ انھیں خوب داد وصول ہوئی۔

                پھر انہوں نے ان کی مدح کے لیے بھی قلم اٹھایااور لکھنا شروع کیااور لکھتے ہی چلے  گئے۔ اس طرح انھوں نے در عدالت علے کو مکمل کیا۔اس کا انتساب اسی...

The Knowledge, Attitude, and Practice about Fertility Preservation among Oncologist-A Cross-Sectional Study

BackgroundFertility Preservation is the process of saving or protecting a person’s ability to have children in the future. It is often considered for individuals to undergo medical treatments that may impact their fertility, such as chemotherapy. Hence, the current study is aimed to assess clinical practitioners’ knowledge, practice, and attitude toward fertility preservation among oncologists. MethodsA cross-sectional survey was carried out to identify the current knowledge, attitudes, and practices regarding fertility preservation among oncologists—a total of seventy-nine oncologists in Karachi working in different public and private sectors. The study was conducted between January to August 2022. The data was gathered using a self-designed questionnaire that was distributed via email. ResultsOne hundred and eighty oncologists were provided with the survey form via email. The response rate was 47.22% (n=85). Out of which, six questionnaires were excluded due to incomplete information. The total questionnaire analyzed was n=79, which included 58 (73.41%) males and 21 (16.59%) females. ConclusionThe results revealed that oncologists had a compromised knowledge regarding fertility preservation for cancer patients. Despite weak knowledge, most oncologists believe that more elaborative measures should be taken to overcome this issue.   DOI: https: //doi. Org/10.59564/amrj/01.01/004

A New Framework to Bridge Semantic Gap for Semantics Based Image Retrieval

The performance of Content Based Image Retrieval (CBIR) is limited because of the Semantic Gap (SG). This motivates to extend the image retrieval process beyond low level descriptions to image semantics. Therefore, researchers proposed Semantic Based Image Retrieval (SBIR) to bridge SG. In the literature, various approaches for SBIR such as image annotation, relevance feedback, and object ontology have been proposed to bridge SG. It has been observed that not very promising results with these methods are reported in the literature. Annotation based approaches are constrained by low precision because real life images usually have a diverse set of image concepts. Relevance feedback approach is also constrained by low precision and recall because it forces to alter the query vector that causes to modify image semantics. Object ontology is a considerably good approach, but its metadata architecture appears to be very complex and suggested to use only for semantic web instead of SBIR. Moreover, this approach is reported to have low precision for conceptually diverse images. Therefore, the first contribution of our work is the performance evaluation of CBIR methods using soft computing techniques for image comparison and retrieval. In this regard, we have reported performance improvement in terms of retrieving visually similar images by employing proposed modifications in soft computing methods. However, these modifications do not translate into semantically correct retrieval of images. This leads us towards the logical conclusion of planning and development of a new SBIR framework using image concepts. By the term “image concept” we means that a set of noticeable objects and regions in an image e.g. Sky, group of person, land etc. In our first contribution we have also explored existing CBIR approaches in order to find a suitable 11 candidate (or its modified version) to be used for SBIR. The second contribution of our work is therefore to bridge the SG with a maximum tradeoff between precision and recall. The proposed framework is extensively examined by evaluating precision and recall for large segmented datasets. For the rigorous testing of our major contributions, three datasets have been opted, namely, Wang’s, COIL, and IAPR TC-12.
Asian Research Index Whatsapp Chanel
Asian Research Index Whatsapp Chanel

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