This study is about exploring student leadership perceptions and practices in a private secondary school in Karachi, Pakistan. The study focuses on student leaders with the purpose to understand their perceptions of leadership as well as to understand non student leaders, who are deprived leadership opportunities. The study is to validate the findings of the student leaders' perceptions and practices of leadership. The study involves secondary student leaders, who are head boy, head girl, captain and prefects in the school. The study also looks at the principal's and the teachers' perceptions of leadership in order to understand the kind of leadership provided and how it influences student leadership practices in the school. The study also highlights the factors that promote or hinder practices of student leadership. The data was collected through qualitative research methods, including semi structured interviews, participant observation, and analysis of school documents, which articulated student leaders' roles and responsibilities. In addition, data was collected from focus group discussion with student leaders and non student leaders. The study found that stakeholders such as student leaders, non student leaders, principal and the teachers perceive leadership to be an individual possession, as something that brings power and possess particular qualities. Their perceptions identify the belief that leadership is the property of an individual, who has power and possesses particular leadership qualities. This belief can greatly influence the prevalent practices of student leadership in the school. The study also found that the practice of student leadership involves organizing and disciplining students in the school. Student leaders were exposed to classroom, as well as co curricular activities in order to develop their leadership skills. However, student leaders do not wield power and do not have voice in decision-making in the school. The study also found the influencing factors, such as school vision, home environment, parent-school partnership, and gender disparities, which can support or hinder practices of student leadership in the school.
جناب مولانا عبداﷲ صاحب غازی پوری کا واقعہ وفات علماء کے طبقہ میں خاص حیثیت سے اثر انگیز ہے، مولانائے مرحوم نے گو طبعی عمر پائی لیکن اس خیال سے کہ وہ اس عہد میں اگلی صحبتوں کے تنہا یادگار تھے۔ ہم ان کے لئے اس سے دراز عمر کے متوقع تھے، مولانا اتباعِ سنت، طہارت تقویٰ، زہد و ورع، تبحرعلم، وسعتِ نظر اور کتاب و سنت کی تفسیر و تعبیر میں یگانۂ عہد تھے، اپنی عمر کا بڑا حصہ انہوں نے علم دینیہ خصوصاً کتاب مجید اور حدیث شریف کے درس و تدریس میں گزارا اور سینکڑوں طلبہ انکے فیض تربیت سے علماء بن کر نکلے، ابتداً چشمۂ رحمت غازیپور میں، پھر مدرسہ احدیہ آرہ میں اپنا مسندِ درس بچھایا، آخر عمر میں دلّی کے دارالحدیث میں قیام فرمایا، لیکن خانگی حوادث کے باعث پریشان حال رہے، اب افسوس کہ یہ شمع نورو ہدایت ۲۱؍ صفر ۱۳۳۷ھ مطابق ۲۶؍ نومبر، ۱۹۱۸ء کو ہمیشہ کے لئے بجھ گئی۔ رحمہ اﷲ تعالیٰ۔
مجھے لکھنؤ میں مولانا عبدالحئی صاحب ناظم ندوہ کی قیام گاہ پر مولانا سے ملاقات کی سعادت ایک دو دفعہ حاصل ہوئی دُبلے، پتلے، نخیف، داڑھی کے بال خفیف، سادی وضع، صورت سے متواضع اور حلیم معلوم ہوتے تھے۔
مرحوم کا اصلی وطن گومؤ ضلع اعظم گڑھ تھا، مگر قیام بیشتر غازی پور میں رہا، اس لئے غازیپوری کے نام سے شہرت پائی، ابتدائی تعلیم چشمۂ رحمت غازی پور میں ہوئی، یہاں مولوی رحمت اﷲ صاحب غازی پوری، اور مولوی فاروق صاحب چریا کوٹی سے پڑھا، پھر جونپور جاکر مدرسۂ امام بخش میں مفتی محمد یوسف صاحب فرنگی محلی سے درسیات پڑھیں اور آخر میں حدیث کی کتابیں مولانا سید نذیر حسین صاحب دہلوی سے پڑھیں اور...
From the very beginning Islam has given great importance to discipline. In every facet of life discipline has a role to play. Today when we delve deep in to our lives, we are amazed as to how it has always proved its worth. It has brought the tide of revolution in everyone's mind. Similarly, the element of discipline saves a society from disruption and instability. It infuses in life satisfaction and contentment. Contrarily, indiscipline and mismanagement give birth to dejection and dissatisfaction. Time management plays a vital role in the establishment of discipline in a society. Considering the vast importance of time management in the light of discipline, the following article throws a great deal of light on it in the Islamic perspective.
Biometric recognition systems are considered to be one of the most secured means of authentication. In this context several biometrics have been proposed but the view based biometrics such as face, iris etc remain the most natural choice. In the paradigm of face recognition, it is generally assumed that major information contents lie in the lower frequency region of an image and therefore little effort has been made in sys tematic exploration of the detail images. Although some wrapper-based approaches have been proposed in the literature, they are primarily based on experimental eval uation of a specific classifier on various subbands. Therefore there is a dire need of a framework for automatic selection of the most significant subbands based on the underlying statistics of the data. In this thesis, the problem of identifying the most dis criminant subbands based on information theoretic measures is addressed. Essentially the face images are transformed into textures using the linear binary pattern (LBP) ap proach, these texturized-faces undergo the wavelet packet decomposition resulting in several subband images. We propose to use the energy features to effectively represent these subband images. The underlying statistical patterns of the data are harnessed in form of information-theoretic metrics to select the most discriminant subbands. The proposed algorithms are extensively evaluated on several standard databases and are shown to always pick the most significant subbands resulting in better performance. The proposed algorithms are entirely generic and do not depend on the validation re sults for specific classifiers. Noting that localized features are often more useful than theholisticapproaches, wehavealsotargetedtheproblemofirisrecognitionproposing the concept of class-specific dictionaries. Essentially, the query image is represented as a linear combination of training images from each class. The well-conditioned inverse problem is solved using least squares regression and the decision is ruled in favor of the class with the most precise estimation. An enhanced modular approach is further proposed to counter noise due to imperfect segmentation of the iris region. As such iris images are partitioned and individual decisions of all sectors are fused using an efficient fusion algorithm. The proposed algorithm is compared to the state-of-the-art Sparse Representation Classification (SRC) with Bayesian fusion for multiple sectors. The proposed approach has shown to comprehensively outperform the SRC algorithm on standard databases. Complexity analysis of the proposed algorithm shows decisive superiority of the proposed approach.