Deep Learning Models for Health and Safety Risk Prediction in Power Infrastructure Projects

Inappropriate management of health and safety (H&S) risk in power infrastructure projects can result in occupational accidents and equipment damage. Accidents at work have detrimental effects on workers, company, and the general public. Despite the availability of H&S incident data, utilizing them to mitigate accident occurrence effectively is challenging due to inherent limitations of existing data logging methods. In this study, we used a text-mining approach for retrieving meaningful terms from data and develop six deep learning (DL) models for H&S risks management in power infrastructure. The DL models include DNN_classify (risk or no risk), DNN_reg1 (loss time), DNN_reg2 (body injury), DNN_reg3 (plant and fleet), DNN_reg4 (equipment), and DNN_reg5 (environment). An H&S risk database obtained from a leading UK power infrastructure construction company was used in developing the models using the H2O framework of the R language. Performances of DL models were assessed and benchmarked with existing models using test data and appropriate performance metrics. The overall accuracy of the classification model was 0.93. The average R² value for the five regression models was 0.92, with mean absolute error between 0.91 and 0.94. The presented results, in addition to the developed user-interface module, will help practitioners obtain a better understanding of H&S challenges, minimize project costs (such as third-party insurance and equipment repairs), and offer effective strategies to mitigate H&S risk.     

State Repression and Religious Conflict: The Perils of the State Clampdown on the Shi’a Minority in Nigeria

In Nigeria, there is an increasing population of the followers of Shi’a Islam, which is largely promoted by the Islamic Movement of Nigeria (IMN) led by Sheikh Ibrahim El-Zakzaky. Given its anti-state ideology and anarchical conducts, there have been a series of clashes between the Shi’a group and the Nigerian state. Since December 2015, the government both at the national and state levels began a coercive repression of the IMN following a clash that led to the death of over 500 members of the group. This paper analyses the ongoing state repression of the Shi’a Muslims in Nigeria. It argues that the increasingly violent actions by the state against the group are a recipe for a large-scale conflict, which may assume the following dimensions: a new wave of religious terrorism (after Boko Haram), a Sunni-Shi’a conflict, and international proxy wars in Nigeria. The paper concludes that a practicable way to stem the imminent violence is for the government to establish a dialogue with the group on how to ensure its compliance with the state laws and not totally outlaw it.