Health Help-Seeking Behavior: The Scavengers' Perspective.

Scavengers are prone to various health problems, hence seeking healthcare is inevitable. Despite the importance of the help-seeking behavior of scavengers, it has not been addressed explicitly in the existing literature. Addressing this gap, this study intends to explore the help-seeking behavior of scavengers and to identify the factors that influence healthcare utilization among them. This qualitative study conducted thirty-one in-depth interviews through a semi-structured interview guide and analyzed them using thematic analysis. Andersen's Behavioral Model of Health Service Use was employed to explore the findings. The findings showed that the scavengers utilized multiple healthcare options depending on the severity and reoccurrence of the illness. The process of help-seeking and health services utilization was largely influenced by the cost of the health service, long distance to the health facility, traveling cost and waiting time. The study highlights the need for scavengers' enrolment in micro health insurance schemes. The initiative would facilitate scavengers' access to medical care. Health awareness campaigns and the provision of free mobile medical services, especially at the landfill sites, would also improve curative treatment among scavengers.

Erratum: Ahmad, S.; Malik, S.; Park, D.-H.; Kim, D. Design of Lightweight Driver-Assistance System for Safe Driving in Electric Vehicles.

The authors wish to make the following erratum to this paper [...].

Design of Lightweight Driver-Assistance System for Safe Driving in Electric Vehicles.

Electric-vehicle technology is an emerging area offering several benefits such as economy due to low running costs. Electric vehicles can also help to significantly reduce CO 2 emission, which is a vital factor for environmental pollution. Modern vehicles are equipped with driver-assistance systems that facilitate drivers by offloading some of the tasks a driver does while driving. Human beings are prone to errors. Therefore, accidents and fatalities can happen if the driver fails to perform a particular task within the deadline. In electric vehicles, the focus has always been to optimize the power and battery life, and thus, any additional hardware can affect their battery life significantly. In this paper, the design of driver-assistance systems has been introduced to automate and assist in some of the vital tasks, such as a braking system, in an optimized manner. We revamp the idea of the traditional driver-assistance system and propose a generic lightweight system based on the leading factors and their impact on accidents. We model tasks for these factors and simulate a low-cost driver-assistance system in a real-time context, where these scenarios are investigated and tasks schedulability is formally proved before deploying them in electric vehicles. The proposed driver-assistance system offers many advantages. It decreases the risk of accidents and monitors the safety of driving. If, at some point, the risk index is above a certain threshold, an automated control algorithm is triggered to reduce it by activating different actuators. At the same time, it is lightweight and does not require any dedicated hardware, which in turn has a significant advantage in terms of battery life. Results show that the proposed system not only is accurate but also has a very negligible effect on energy consumption and battery life.