سکھ دھرم پر اسلامی تعلیمات کے اثرات کا علمی جائزہ

Sikhism is one of the Non Semitic religions founded by Guru Nanak, belonged to a Hindu family and was born in 1469 A.D. This religion is popular in India and Pakistan. Some inhuman customs in Hinduism like caste system, the custom of Satty (burning out of wife with the dead body of husband), monopoly of Brāchman etc. Compelled him to introduce a new religion based on equality and justice. As identified from the life style of the founder of Sikhism and his followers, he is deeply impressed with Islamic teachings. Their habits and customs reflect an Islamic picture. Guru Nanak was a monotheist and was against the worship of idols. He believed in equality and acknowledged the prophet Muhammad (S.A.W), as a role model for human beings. This article is aiming to explain the teachings of Sikhism derived from Islam.

A Framework to Predict the Student S Performance in Programing Courses

Academic grades prediction is considered as one of the hot research areas since last decade, which comes under the domain of educational data mining. It has been observed that in undergraduate computer science programs, programming courses are considered challenging. This results in higher tendency of earning lower grades, failures or drop-outs than other computer science subjects. An early prediction of the students who have high probability of failure (known as at-risk students) will enable the instructors to intervene and provide extra guidance to learners. An accurate prediction of student?s grades can directly influence the overall quality of any degree program and the retention rate of the institution. This research presents a machine learning based classification model for undergraduate students grades prediction, enrolled in any programming course(s) in traditional education system. The proposed model is built after careful collection and pre-processing of data, appropriate feature selection, and model evaluation based on four metrics namely accuracy, precision, recall and F1-score. Six widely used supervised machine learning techniques including Random Forest, Artificial Neural Network, K-Nearest Neighbors, Na?ve Bayes, Ordinal Regression, and Support Vector Machine are used after tuning and optimization. The data used for this research is collected from a private sector university in Lahore. The collected data covers two major domains: student?s academic record and demographic data. The results show that Support Vector Machine and K-Nearest Neighbors give highest scores (ranging from 81% to 94%) for all the evaluation metrics and for all the seven programming courses considered for this study.