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البــاب الثالث: دراسة الأدب القراني الكريم في آثار مصطفی صادق الرافعي

الفصــل الأول: اعجاز القرآن وبلاغة النبوية

أن الألفاظ القران منزلة بحروفها ونسقها والابطل الاعجاز لأن الاعجاز لا يكون انسانيا وقد كان الوحي ينزل علي النبي صلي الله عليه وسلم فتعتريه حالة روحية وردت صفتها في البخاري و غيره.

قال سعد باشا زغلول في رسالته الذي كتب إلی الرافعي عن تقريظ كتاب اعجاز القران:

تحدي القران أهل البيان في عبارت قارعة محرجة ، ولهجة واخزة مرغمة أن يأتو بمثله أو سورة منه ، فما فعلوا ، ولو قدروا ماتأخروا لشدةحرصهم علي تكذيبهم و معارضته بكل ما ملكت أيمانهم واتسع له امكانهم ،هذا العجز الوضيع بعد ذاك التحدي الصارخ هو أثر تلك القدرة الفائقة ، وهذا السكون الذليل بعد ذاك الاستفزاز الشامخ هو أثر ذلك الكلام العزيز فجاءكتابكم ’’اعجاز القران ‘‘مصدقا لاياتها مكذبا لانكارهم وأيد بلاغة القران واعجازها بأدلة مشتقة من أسرارها في بيان مستمد من روحها ’’كانه تنزيل من التنزيل أو قبس من نور الذكر الحكيم‘‘([1])

وقال أيضاً عن تقريظ اعجاز القران والبلاغة النبوية شبَّه فيه أسلوب المؤلف بالتنزيل الحكيم، وهو تشبيه يصور حقيقة كبيرة، فإن الرافعي يتأثر في نثره العبارة القرآنية في بلاغتها وسموها.([2]) أن القرآن معجزة هذه في بلاغة نظمه واتساق أوضاعه وأسراره، فمن ثم كانت مادة الاتصال في نسق التإلیف بين هذا الجزء والذي قبله. القرآن الكريم مما يتعلق بلغته ويتصل ببلاغته ويكشف عن أوجه الإعجاز في ذلك، لا ننفذ في غير سبب لما نحن بسبيله، ولا نذهب في الكلام عن نتيجة من نتائجه. ولقد أراد الله أن لا تضعف قوة هذا الكتاب، وأن لا يكون في أمره على تقادم الزمن خَضغ أو تَطامن، فجاءت هذه القوة فيه بأسبابها المختلفة على مقدار ما أراد، وهي قوة الخلودالأرضي التي خرج بها القرآن مخرج الشذوذ الطبيعي، فلا سبيل عليه ليد الزمن وحوادثه مما تُبليه أو تستجدُّه، إنما هو روحٌ من أمر الله تعالى هو...

خاندانی نظام میں تربیت اخلاق: سیرت النبیﷺ کے تناظر میں

Family is the only institution where the nations are built. Basic moral values are also taught by the family. Manners, ethics and moral values has great importance in islam. That’s why Hazrat Muhammad (PBUH) was sent to uphold and uplift ethical values. Being the role model for humanity in all affairs, seerah of Muhammad (PBUH) also provides guidance how to teach ethics and moral values in a family system. This paper will highlight the Prophetic method of teaching ethics and moral values in a family setup.

Fast Video Encoding Using Spatio-Temporal Features and Ensemble Classification

Video Coding has evolved over the years and new compression standards are being developed at regular intervals. Latest video codecs such as High Efficiency Video Coding (HEVC) have improved compression efficiency to reduce the bit-rates of en coded streams. This improvement has resulted in high computational complexity that becomes a bottleneck in real-time implementation of these codecs. Reduction in this computational complexity without compromise on the video quality is a challenge. Another challenge in fast video encoding is the diverse nature of video content. Hence, there is need for development of intelligent techniques to reduce the computational complexity of latest video codecs that also adapt to the diverse nature of video data. Research in this thesis focuses on identification of local and global features ex tracted from video data that can be used to characterize the diverse content in video sequences. Texture variations and motion content in video sequence are quantified to categorize it into simple and complex video sequence. This informa tion is used to develop a content adaptive fast encoding framework to reduce the computational complexity of HEVC. Proposed framework performs equally well both for sequences with simple or complex video content without compromising on video quality. It has been tested with a large set of video sequences and shows promising results as compared to the other recent works. This research work also focuses on the use of machine learning based algorithms for fast encoding to significantly reduce the complexity of video codecs while keeping bit-rate and PSNR within limits in recent video standards like HEVC. Machine learning based techniques formulate encoding process as a classification problem and use features extracted from video data to model the classifiers that can assist in early predictions during encoding. A large set of spatial and temporal features is extracted from video data and a systematic approach is applied for optimal feature selection. Resultant optimal features are used to train a Random Forests based ensemble classifier for early selection of prediction modes and coding unit sizes in HEVC. Proposed technique has been evaluated with publicly available video data x sets. Experimental results show that the proposed approach significantly reduces the complexity of different profiles in HEVC without compromising on video qual ity and performs better than other existing fast video encoding implementations. Fast encoding methods developed in this research have also been validated using emerging applications of HEVC such as compression of light field images. Detailed analysis of different formats in light field image representation has been carried out to identify unique aspects that differentiate them from natural videos. These unique features are used in fast coding of light field images in various formats using HEVC. Experimental results show that proposed technique can be applied in fast coding of light field images without compromise on image quality. These results can be used as benchmark for future research on fast encoding of light field images. Hence, the fast video encoding methods developed in this research can be extended to other applications of image and video coding. These techniques can also be integrated in real life video encoding solutions to enable implementation of latest video codecs on embedded hardware platforms with limited processing power and memory.
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