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اٹھائے کچھ ورق

          آ ج تک ادبی تناظر میں سیالکوٹ کے حوالے سے جب بھی بات ہوئی، جب بھی قلم اٹھایا گیا، جب بھی کوئی صدا بلند ہوئی شعری ادب ہی طبع آ زمائی کا موضوع ٹھہرا۔ یہ پہلی دفعہ ہے کہ '' تاریخ ادبیات سیالکوٹ'' کے ذریعے ڈاکٹر نصیر احمد اسد کے زشحات قلم نے شاعری،نثر، تنقید اور اقبال شناسی چار پہلوؤں پر نقد و نظر کی ہے۔ یہ کتاب بطور خاص ڈاکٹر صاحب کے پی ایچ ڈی مقالہ '' سیالکوٹ میں نقدو ادب کی روایت'' کے اس سفر کا تسلسل اور سنگ میل ہے جس کا آ غاز ان کے ایم فل کے مقالہ سے ہوا تھا۔ ڈاکٹر صاحب اس مقالے کے ذریعے قبل مسیح سے آ ج تک کے تعلیمی مرکز اقبال کے سیالکوٹ کے بارے میں شجر طہر انی کی طویل تاریخی نظم ''سالباہن کی نگری '' کو منظر عام پر لانے کا شکریہ، برناباس کی انجیل کے گم شدہ انگریزی ترجمہ کے اردو مترجم استاد مکرم آ سی ضیائی رام پوری کو بھی یاد کرنے کا شکریہ۔ آ سی ضیائی کے حوالے سے آ پ نے کیا خوب لکھا ہے۔'' آ سی ضیائی رام پوری بھی اپنی شاعری اور نثر میں حمدیہ اور نعتیہ لہجہ رکھتے ہیں۔ آ پ کی نعتیہ نظموں میں منفرد اسلوب اظہار،ندرت بیان اور فکری و جذباتی اپیل پائی جاتی ہے۔ ایک عاشق رسول ہونے کے ناطے آ پ کی تب و تاب اور سوز و ساز عمل کا ایک پیغام ہے''

          ڈاکٹر صاحب نے صدیوں کی تہیں کھول کر اہل سیالکوٹ کی خدمات کے خزانے بر آ مد کئے ہیں۔ اس کتاب کے توسط سے ہم کشمیر پر بھارت کے غاصبانہ قبضہ کے خلاف مزاحمتی ادب تخلیق کرنے والے سیالکوٹ کے ادیبوں کو بھی سلام پیش کرتے ہیں۔

          سیالکوٹ میں

فلسطینی مستضعفین کی عصری صورتحال ایک جائزہ

The Muslims of today are overwhelmed and subjugated all over the world due to the bad intensions of colonizers. They are now called the oppressed people in the world. Especially the Muslims of Palestine are the main target of these colonialists, as Palestine is the controversial issue between the Muslims, Christians and Jews. It is the holy and sacred place for all of them. The Jews consider this place as their birthright and also due to their political and social self-interests they always tried to get their hold there by the oppression of Palestinian Muslims. The illegal Israeli (jews) state in Jerusalem is constantly oppressing the Muslims of Palestine. Due to this oppression these Palestinian Muslims are also called the oppressed people in the world. Today this problem of oppression in Palestine is more surpassing. Israeli (jews) people are persistently killing and forcing the muslims to leave this country. Palestinians are now immigrants and seekinf refuge from different countries but unhappily they are also in trouble and in pathetic condition. They are just helpless and even deprived of their basic rights. Keeping in view this scenario, in this article a brief review is given about the history and the present situation of oppression on Palestinian Muslims

Machine Learning Based Approach for Facial Expression Classification

Facial expressions deliver intensive information about human emotions and the most valuable way of social collaborations, despite difference in ethnicity, culture, and geography. These differences addresses the three main problems, which are; facial appearance variation, facial structure variation, and inter-expression resemblance. Due to these problems the existing facial expression recognition techniques are very inconsistent. This study presents several computational algorithms to handle these problems in order to get high expression recognition accuracy. We proposed a novel ensemble classifier for cross-cultural facial expression recognition. The proposed ensemble classifier consists of three stages; base-level, meta-level and predictor, where binary neural network adopted as base-level classifier, neural network ensemble (NNE) collections as meta-level classifier and naive Bayes (NB) with Bernoulli distribution as predictor. The NB classifier takes the binary output of NNE collections and classifies the sample image as one of the possible facial expressions. The Viola-Jones algorithm is used to detect the face and expression concentration region. The acted still images of three databases JAFFE, TFEID, and RadBoud originate from four different cultures are combined to form multi-culture facial expression dataset. Three different feature extraction techniques LBP, ULBP and PCA are applied for facial feature representation. Further, boosted NNE collections are developed to enhance the facial expression recognition accuracy. The proposed boosting technique combines multiple NNEs which are complement to each other. The combination of boosted NNE collections with HOG-PCA feature vector perform significantly better than NNE collections. Later on the multi-culture dataset is extended by adding more cultural diversity from KDEF and CK+ databases, which is used to train the SVM based ensemble collections. The introduction of SVM ensemble collections at meta-level provides strong generalization ability to learn the vast variety of cultural variations in expression representation. Moreover, sensitivity analysis and inter-expression resemblance analysis are performed to quantify the level of complexity in cross-cultural facial expression recognition. It shows that expressions of happiness, surprise and anger are easy to recognize as compare to expressions of sadness and fear. It proves that these expressions are innate and universal across all cultures with minor variations. The experimental results demonstrate that proposed cross-cultural facial expression recognition techniques perform significantly better than state of the art techniques.
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