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میں صحنِ دل کے پت جھڑ کو بہارِ جاوداں کر لوں


میں صحنِ دل کے پت جھڑ کو ، بہارِ جاوداں کر لوں
محبت جانِ عالمؐ کی ، اگر روحِ رواں کر لوں

غم و آلامِ دنیا سے ، ذرا سا بھی جو گبھرائے
تو یادِ مونسِ جاںؐ سے ، میں دل کو شادماں کر لوں

سجائی بزمِ عالم ؛ جنؐ کی خاطر ؛ خالقِ کُل نے
اُنھیؐ کا ذکر کرنے کو ، میں بزمِ دوستاں کر لوں

سمائی نکہتِ بادِ بہاری میں مہک جنؐ کی
اُنھیںؐ سے خوشبوئیں لے کر میں دل کو گلستاں کر لوں

یہی سالک کو لے کر جا رہا ہے منزلِ حق پر
اسی نقشِ قدم کو چوم کر ، منزل نشاں کر لوں

اِدھر کر لوں زبانِ اشک سے عرضِ تمنا بھی
اُدھر چشمِ تصور میں سنہری جالیاں کر لوں

ادب گاہِ عقیدت میں کہاں الفاظ جچتے ہیں
’’طریقہ سب سے بہتر ہے کہ اشکوں کو زباں کر لوں‘‘

دلِ بے تاب کے لمحات اُنؐ کی یاد میں گزریں
جہانِ رنگ و بُو میں کیوں انھیں میں رائیگاں کر لوں

دلِ فرقت زدہ عرفانؔ! اُنؐ کے ذکر سے خوش ہو
میں صبح و شام اُنؐ کے نام کو وردِ زباں کر لوں

PARADIGMA BARU PENDIDIKAN KONTEMPORER DI INDONESIA

Education is a series of processes of human empowerment towards maturity, both intellectually, mentally and morally, to carry out the humanitarian function carried as a servant (abd) in front of his Khaliq and as a "preserver" (caliph) in the earth. The position of contemporary education in the midst of the spirit of national education reform, of course it is necessary to look at the meaning and role of contemporary education in this national life. Similarly, in order to find a new paradigm of contemporary education, it should begin with the existence of Islamic education in the history of national and state life. And in developing the quality of contemporary education, of course it is necessary to pay attention. First, education is increasingly demanded to appear as emerging in the development of the quality of human resources (output of education). Second, in the perspective of the world of work, an orientation to real abilities (what one can do) that can be displayed by very strong education graduates Third, as a result of globalization.

An Adaptive Classification and Recommendation Model for E-Health

FACULTY OF TELECOMMUNICATION AND INFORMATION ENGINEERING Department of Software Engineering Doctor of Philosophy An Adaptive Classification and Recommendation Model for e-Health Systems By Anam Mustaqeem 13F-UET/PhD-SE-06 E-health based system is an advanced topic of research, showing an enormous amount of effort for providing an efficient response to cardiac diseases. Health monitoring of patients in particular senior citizens at their home based location is categorized among the wide ranged applications of today’s health care systems. Health professional track the clinical condition of elderly patients at remote locations using monitoring devices, which otherwise would have to admit to a medical caring unit. The purpose of e-health is to highlight the issues regarding health care and therefore, reduce the chances of hospitalization, help in improving quality of life style, and saving money. With the advent of e-health, the information about most critical issues of patients can be accessed from far away locations. A promising and active research area, which has benefited from the e-health based system is cardiac monitoring and care. In this research work, we intend to develop an adaptable and intelligent recommendation based model for e-health systems. As cardiac diseases are one of most critical and life threatening disease among chronic diseases, therefore cardiac disease classification and iv recommendation is addressed in this study. The research work has been categorized into three different areas. The results have been evaluated using standard evaluation metrics and an improved accuracy is obtained in all research tasks. A model is proposed using a standard dataset for arrhythmia classification to provide improved classification accuracy. The approach for classification combines feature selection, pre-processing and classification techniques, and provides promising diagnosis results. Further, normalization is done for scaling and standardizing the data parameters. An improved feature selection method using a wrapper method around the random forest (RF) is employed to select the most significant features achieving higher classification accuracies for the UCI arrhythmia dataset. The selected features help in achieving better accuracy and efficient classification performance. In the second part of the thesis, the details are presented for collection, analysis and processing of a customized dataset to implement recommender system for cardiac patients under the supervision of medical experts. Although recommender systems have emerged in various domains, development of a clinically apporoved medical recommender systems still require a long way to go, as medical recommendations directly affect the life of patients. We have proposed a hybrid machine learning based prediction and risk analysis based recommendation model for detection of heart disease which provides suitable medical advice to a patient depending on the type of disease identified. The results show that the proposed medical recommender system will be a significant contribution in the field of cardiac disease classification and recommendation. A medical recommender system is implemented using a modular clustered based collaborative filtering model, which is an improvisation in the traditional collaborative filtering technique to target the issues of sparsity and scalability. Sub-clustering at two levels is introduced to ensure fast and robust similarity computations. The involvement of cardiac experts in the whole process is made possible for clinical approval and disapproval of the outcomes.
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