Between war and peace : the Afghanistan essays

“This 2018 short-essay series by the Jinnah Institute (JI) reflects a range of Pakistani thought leadership on Afghanistan and it’s complex history with Islamabad. With the region in the current crosshairs of a seemingly intractable conflict, these essays attempt to spur old and new thinking on the history of Pakistan’s relationship with Afghanistan and existing challenges. The essays cover a range of subject matter on Afghanistan-Pakistan including efforts for peace and reconciliation, threats to security, the broader geopolitical dynamic, and the role of civil society and economy. This essay titled ‘Enemy at the Gates: The TTP in Afghanistan’ examines the threat posed to Pakistan by the TTP from their terror sanctuaries in Afghanistan. It explores Pakistan’s strategic anxieties and what can be done to address them.

A feature-centric spam email detection model using diverse supervised machine learning algorithms

Purpose This research study proposes a feature-centric spam email detection model (FSEDM) based on content, sentiment, semantic, user and spam-lexicon features set. The purpose of this study is to exploit the role of sentiment features along with other proposed features to evaluate the classification accuracy of machine learning algorithms for spam email detection. Design/methodology/approach Existing studies primarily exploits content-based feature engineering approach; however, a limited number of features is considered. In this regard, this research study proposed a feature-centric framework (FSEDM) based on existing and novel features of email data set, which are extracted after pre-processing. Afterwards, diverse supervised learning techniques are applied on the proposed features in conjunction with feature selection techniques such as information gain, gain ratio and Relief-F to rank most prominent features and classify the emails into spam or ham (not spam). Findings Analysis and experimental results indicated that the proposed model with sentiment analysis is competitive approach for spam email detection. Using the proposed model, deep neural network applied with sentiment features outperformed other classifiers in terms of classification accuracy up to 97.2%. Originality/value This research is novel in this regard that no previous research focuses on sentiment analysis in conjunction with other email features for detection of spam emails. </jats:sec

Islamic economics: a survey of the literature

A central thesis of this paper is that social science is the study of human experience, and hence is strongly conditioned by history. Modern Western political, economic and social structures have emerged as a consequence of the repudiation of religion associated with the Enlightenment and are based on secular principles. Many of these are inimical to Islamic principles, and cannot be adapted to an Islamic society. Muslim societies achieved freedom from colonial rule in the first half of the twentieth century and have sought to construct institutions in conformity with Islam. The development of Islamic economics is part of this process of transition away from Western colonial institutions. This paper is a survey of the literature on Islamic economics, which focuses on the contrasts between Western economic theories and Islamic approaches to the organization of economic affairs