سی حرفی ۔۸
(تن بیتاں وچ مکمل)
الف
آماہی، ’ب‘ بہت تھکی، ت تاہنگ تیری پئی مار دی اے
ث
ثابتی نہیں، ’ج‘ جگر باہجوں، ’ح‘ حالت گئی گھر بار دی اے
خ
خوشی گئی، ’د‘ دکھ بہتے، ’ذ‘ ذکر تے فکر سب یار دی اے
ر
رب وارث، ’ز‘ زاریاں دا، ’س‘ سک حنیف دیدار دی اے
ش
شوق لگا، ’ص‘ صادقاں دا، ’ض‘ ضعف نہیں کجھ نتار دا اے
ط
طوق پیا، ’ظ‘ ظالماں دا، ’ع‘ عاشقاں ہانگرا دار دا اے
غ
غم لگا، ’ف‘ فکر ڈاہڈا، ’ق‘ قسم مینوں شوق یار دا اے
ک
کون کٹے، ’ل‘ لکھ دتا،’م‘ مویاں نوں یار کیوں مار دا اے
ن
نیہہ ڈونگھی، چڑھی گھٹ کالی، اساں لنگھنا پہلڑے پور یارو
و
واہ کوئی نہیں، ہور راہ کوئی نہیں، ’ہ‘ ہڑ دا سماں ضرور یارو
لا
لا مکان دا پتہ دسے، ’ی‘ یاد نہ مان غرور یارو
ے
یار حنیف بھلائی دنیا، کیڈ پائے نیں عشق فتور یارو
٭٭٭٭٭٭
It is with great pleasure that I write this editorial to welcome you to the first issue of this new International journal, “Pakistan Biomedical Journal” (PBMJ). The topics covered by the journal are certainly broad and interesting. Biomedical science is a collection of applied sciences that help us understand, research, and innovate within the field of healthcare. It includes disciplines like molecular biology, clinical virology, bioinformatics, and biomedical engineering, among others. It's designed to apply the biological sciences to advance not only individual health but also the area of public health. Biomedical Research can help health professions better understand things like the human body and cell biology, making advances in our understanding of epidemics, health initiatives, and human health in the age of longer life expectancy. It aids our understanding of infectious disease and provides research opportunities into some of our most troubling health issues. The journal will continue to publish high quality clinical and biomedical research in health and disease later in life. Peer review will remain a vital component of our assessment of submitted articles.I am very happy to have a team of excellent editors and editorial board members from the top international league covering in depth the related topics. They will ensure the highest standards of quality for the published manuscripts and, at the same time, keep the process time as short as possible. We hope to bring best researches in the field of biomedical sciences that may serve as a guideline in health awareness, understanding the mechanisms and its management in future. We definitely look forward to receiving your excellent studies to making PBMJ synonymous with high quality in the biomedical science domain.
Sign language is the language of visual gestures that are mainly used as a communication tool by deaf community. Sign languages use visual pattern that are used to communicate rather than acoustic patterns that are used in verbal communication. Sign language can be a benchmark for gesture recognition system as it is the most structured and developed form of gestures. Automated Sign Language Recognition (SLR) has very effective uses in many real world domains. There are many applications of SLR in the field of robot control, interactive learning, appliances control, virtual reality, simulations, games, industrial machine control, and many more apart from its significance for hearing impaired community. Sign language is not an international language as sign languages are not uniform throughout the world. Like verbal languages, sign languages also differ from region to region and country to country. Pakistani Sign Language (PSL) is a visual-gestural language that came out as a blend of urdu, national language of Pakistan, and other regional languages. The thesis presents a novel, robust, reliable, systematic and consistent system for static PSL recognition. The thesis is based on the empirical evaluation of different potential sign descriptors. The pragmatic approach has lead to a mathematical sign model that has given convincing performance for PSL recognition in terms of accuracy. The polynomial parameterization is proposed as the sign model for PSL recognition. The inherent uncertainty of the domain of sign language demands a classification tool that respects this uncertainty. Because of this very reason, the fuzzy inference got the prominent lead when experimentally compared with other competing classifiers. The main contributions of the thesis are: the development of PSL dataset, robust and efficient sign descriptor and a fuzzy rule based inference model as classifier. There is no standard dataset available for PSL, so dataset for a subset of static signs of PSL is developed for the thesis. An empirical mathematical sign model is presented that has shown its supremacy when analyzed in comparison with other potential sign descriptors. This mathematical model defines every sign of xii the PSL dataset as a polynomial parametric model. For the classification of an uncertain domain like SLR, the conventional classifiers could not come up with sound results. So a fuzzy rule base is proposed for PSL recognition based on polynomial parameters of every individual sign. The meticulous statistical analysis of the proposed PSL Fuzzy Model (PSL-FM) has shown very convincing results.