پاکستانی معاشرے میں تاخیر سے شادیوں کا اسلامی نقطہ نظر سےجائزہ

Family is the basic unit of human society which forms in the shape of marriage between a couple. Historically, all human civilizations and religions have cared for the union between Man and woman by constituting norms and rules right from the solemnization till the death of any partner of the union. Similarly, the religion of Islam has provided all sort of guidance in this regard keeping in view the natural sensations of humans for cohabitation and making their lives pure as well as chaste. Generally, Islam does not encourage late or delayed marriages rather it incites its followers to marry at appropriate time after adulthood. However, nowadays trend of late and delayed marriages is getting popularity in our Pakistani society which is a point of deliberation for the social scientists and Muslim scholars. The current paper deals with this topic to elaborate its causes and suggests means for tackling in the light of Islamic instructions.

Diagnostically Lossless Compression of Medical Images

Medical images are very important for diagnostics and therapy. However, digital imaging generates large amounts of data which need to be compressed, without loss of relevant information, to economize storage space and allow speedy transfer. In this research three techniques are implemented for medical image compression, which provide high compression ratios with no loss of diagnostic quality. Different image modalities are employed for experiments in which X-rays, MRI, CT scans, Ultrasounds and Angiograms are included. The proposed schemes are evaluated by comparing with existing standard compression techniques like JPEG, lossless JPEG2000, LOCOI and Huffman Coding. In a medical image only a small region is diagnostically relevant while the remaining image is much less important. This is called Region of Interest (ROI). The first approach compresses the ROI strictly losslessly and the remaining regions of the image with some loss. In the second approach an image is first compressed at a high compression ratio but with loss, and the difference image is then compressed losslessly. Difference image contain less data and is compressed more compactly than original. Third approach exploits inter-image redundancy for similar modality and same part of human body. More similarity means less entropy which leads to higher compression performance. The overall compression ratio is combination of lossy and lossless compression ratios. The resulting compression is not only strictly lossless, but also expected to yield a high compression ratio. These techniques are based on self designed Neural Network Vector Quantizer (NNVQ) and Huffman coding. Their clever combination is used to get lossless effect. These are spatial domain techniques and do not require frequency domain transformation. i An overall compression ratio of 6-14 is obtained for images with proposed methods. Whereas, by compressing same images by a lossless JPEG2K and Huffman, compression ratio of 2 is obtained at most. The main contribution of the research is higher compression ratios than standard techniques in lossless scenario. This result will be of great importance for data management in a hospital and for teleradiology.