It is a story of just some decades ago. The West used to declare vulgar women and girls as:
- Prostitutes
- Minx
- concubines
- pervert
- misbegotten
- strumpets
- whores
- Hookers
- coquettes
- floozy
- courtesans
- mistress
- cohabitee
- paramour
- Minx
- Pimp
- incestuous
- hussy
The words were inserted by them right in their dictionaries...
Happy life with chest and purity by the way of NIKAH is based on best marital relationships. If there is no mutual love, affection and complete harmony in the marriage life, then the life of wife and husband become very difficult to maintain. This is one of the key feature of Islam that it has made humans responsible for mutual rights and responsibilities and bound them to follow rules and regulations. By doing so the decent nations of the whole world either Muslims or non-Muslims can achieve countless benefits of the marital status. Therefore, the divorce which the messenger of Allah (peace and blessing of Allah be upon Him) has declared as “Most hated act” in lawful and legitimate acts near the Almighty Allah, must be avoided, even if potential or should be minimized in our society. There are many causes of divorce in our Pakistani society and among the significant lake of proper religious education and guidance, family and domestic disputes, complex judicial system, exchange marriage, negative role of media, adverse effects of cellular phones, improper usage of Internet, extreme and excessive use of social media, second marriage, undue obedience of parents and drug addiction are included. This article not only indicates the significant causes of divorce in Pakistani society but also describes the details of their procurement. If corrective measures are taken for these root causes, there is a high hope that the divorce rate will be clearly reduced.
This thesis presents an online handwritten character recognition system for Urdu handwriting. The main target is to recognize handwritten script inputted on the touch screen of a mobile device in particular, and other touch input devices in general. Urdu alphabets are difficult to recognize because of inherent complexities of the script. In a script, Urdu alphabets appear in full as well as in half-forms: initials, medials, and terminals. Ligatures are formed by combining two or more half-form characters. The character-set in half-forms has 108 elements. The whole character-set of 108 elements is too difficult to be classified accurately by a single classifier. In this work, a framework for development of online Urdu handwriting recognition system for smartphones has been presented. A pre-classifier is de signed to segregate the large Urdu character-set into 28 smaller subsets, based on the number of strokes in a character and the position and shape of the diacrtics. This pre-classification allows to cope with the demand of robust and accurate recognition on processors having relatively low computational power and limited memory available to mobile devices, through banks of computationally less com plex classifiers. Based on the decision of the pre-classifier, the appropriate classi fier from the bank of classifiers is loaded to the memory to achieve the recognition task. A comparison of different classifier-feature combinations is presented in this study to exhibit the features’ discrimination capability and classifiers’ recognition ability. The subsets are recognized with different machine learning algorithms such as artificial neural networks, support vector machines, deep belief networks, long short-term memory recurrent neural networks, autoencoders-support vector machines, and autoencoders-deep belief networks. These classifiers are trained with wavelet transform features, structural features, and with sensory input val ues. Maximum overall classification accuracy of 97.2% has been achieved. A large database of handwritten Urdu characters is developed and employed in this study. This database contains 10800 samples of the 108 Urdu half-form characters (100 samples of each character) acquired from 100 writers.
