ماں کی شان
نحمدہ ونصلی علی رسولہ الکریم امّا بعد فاعوذ بااللہ من الشیطن الرجیم
بسم اللہ الرحمن الرحیم
معزز اسا تذہ کرام اور میرے ہم مکتب ساتھیو!
آج مجھے جس موضوع پر اظہار خیال کرنا ہے وہ ہے:’’ماں کی شان ‘‘
صدرِ ذی وقار!
ماں کا نام جب زبان پر آتا ہے تو جسم کالواں لواں سراپا ادب واحترام بن جاتا ہے۔ دل میں ماں کی محبت کی شمع روشن ہو جاتی ہے، تمام بدن عجز وانکساری کے جذبات سے معمور ہو جاتا ہے، روح انسانی طراوت اور تازگی محسوس کرتی ہے اور زندگی کی گاڑی شاہرا ہ حسن و جمال پر رواں دواں ہو جاتی ہے۔
صدرِ محترم!
ماں کیا ہے، ماں ایک گلشنِ حیات کا تر و تازہ گل سر سبز ہے جس پرکبھی پژمردگی نہیں چھاتی ، ماں ایک ایسا بار آور شجر سایہ دار ہے جو کبھی خزاں آشنا نہیں ہوتا، ماں ایک ایسی شمع مستنیر ہے جس کا روح پروانوں کی طرح طواف تو کرتی ہے لیکن جل کر راکھ نہیں ہوتی۔
محترم صدر!
ماں ایک صنف نازک ہے، جو ایک وقت میں اپنے باپ کی گود میں ہوتی ہے، جس پر ایک وقت ایسا بھی آتا ہے کہ بھائی اس کے سر پر دستِ شفقت رکھتا ہے، زندگی کے حسین وجمیل لمحات وہ بیوی بن کر بھی گزارتی ہے۔ لیکن وہ ساعتیں جو اسے مناصب ِرفیعہ پرمتمکن کرنے کا باعث بنتی ہیں وہ صرف اسے ماں بن کر ہی حاصل ہوتی ہیں۔
معزز سامعین!
قرآن و حدیث عظمت ِماں کے شاہد ہیں ، تمام رشتے مقدس ہوتے ہیں۔ والد کا رشتہ عظیم ہوتا ہے، یہ گھر کا سربراہ ہوتا ہے، سارے گھر کی ذمہ داری اس پر ہوتی ہے، بچوں کی تربیت کا مرحلہ ہو، خاندانی امور اپنانے کی بات ہو، باہمی لین دین ہو، عزیز و...
Foreign Exchange trading is when you buy and sell foreign currencies to generate profit. In our age of advance technology even the virtual or digital currencies have now emerged. This entire business however is mostly based upon speculation and prediction. Even the most skilled and experienced traders face difficulty in predicting movements in currencies. Further, the value of not well established currencies can fluctuate or its exchange rate value can change any time. In view of occupying central place in the economic systems down the ages, Muslim scholars have also vehemently discussed currency, its significanc and matters relating to it in transactions. The present article reviews trading of foreign currencies from Islamic perspective in a situation when no cash is involved in the transaction. The article concludes that as the currencies in such transactions are different commodities, therefore their trade is legal.
The expansion of the data is so rapid in the real world today that, now accumulating and processing it is a huge task. This growth is exponential and when Data Mining (DM) tools are applied to analyze this enormous data, it makes the algorithms time-consuming and expensive. One of the most important algorithm in DM for analyzing the data is the tool for classi cation. Classi cation is a function of DM for predicting the class of a sample by building a classi er or a prediction model on the basis of already collected samples with their class. The dataset used for classi cation is a supervised data with di erent features or attribute. During classi cation some features can be of great signi cance while some could be irrelevant and redundant. The learning and prediction time of classi cation algorithms is reduced using feature selection. This decrease in time is due to the time saved on the cost of features that are not selected through feature selection. Feature selection also provides understanding into the nature of the problem to be solved. So, there is a vital need of removing those irrelevant and redundant features before building a classi er. This research is based on solving the problem of feature subset selection (FSS) that chooses the features/attributes that are of signi cant value for the classi er to be built. These signi cant features would reduce the data that will eventually help to improve the accuracy and reliability of big data analytics. The reduction of data eventually would increase the accuracy and reliability of decision support systemsespeciallycriticalhealthrelateddecisionsupportsystems. Other areas include sentiment analysis, opinion mining, drug discovery, tumor detection, stroke detection and many other such applications. Therst phase of this research has the novelty of considering FSS prob lem as multi-objective problem and solving it using two metaheuris tic techniques that are Non-dominating Sorting Genetic Algorithm II (NSGA-II) and Multi-objective Particle Swarm Optimization altered to solve FSS as a binary problem (BMOPSO). The experimentation results represent the importance of considering FSS as multi-objective problem as it outperforms against current techniques of FSS not only in terms of the accuracy of a classi er but number features reduced. The sec ond phase of this research explores Ant Colony Optimization (ACO) technique for FSS which is another meta-heuristic technique. To fur ther re ne the search, the signi cance of each feature is measured using minimum Redundancy Maximum Relevance (mRMR) technique before applying ACO. The results show that proposed technique performs bet ter when compared with other existing biological inspired algorithms for FSS. Both of the phases of this research use di erent real world datasets taken from UCI machine repository and k-fold cross validation is used to further authenticate the results of the proposed techniques. The fea ture subset selection primarily deals with the data representation for the classi cation process and reduces the computational complexity and prediction accuracy.