No abstract

Power consumption, latency, and complexity are considered to be a benchmark for comparing Medium Access Control (MAC) protocols in Wireless Sensor Networks (WSN). However, the importance of these elements varies according to the application. In this paper, three MAC protocols are proposed for forest fire detection. Basically, two of these protocols are based on the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol with some modification to suit the forest fire detection application. These protocols are called Persistent CSMA (P-CSMA) and Per Hope Synchronization CSMA (PHS-CSMA). The third one is a Time Division Multiple Access (TDMA)-based protocol, called Sensor TDMA (S-TDMA). These three protocols are investigated and analyzed by simulation. Results show that there is no superior protocol which outperforms others in terms of power consumption, delay and complexity. However, a trade-off does exist. In terms of power consumption, S-TDMA outperforms other protocols but it has the worst performance in terms of delay. On the other hand, considering the design complexity, S-TDMA is the most complex as it needs time synchronization over the entire cluster while PCSMA and PHS-CSMA don't require time synchronization between nodes.

Paracetamol is an analgesic and an antipyretic most commonly used for headaches and mild fever. It is very common and almost every individual on this planet has consumed paracetamol at least once in his/her life. So, with that high usage, there is need of a high and efficient production from a paracetamol production plant. In this paper, the manufacturing process of paracetamol is simulated and optimized using the software DWSIM. As paracetamol is one of the most used medicines, therefore its production is also very high. But if production is high then there is a chance that the process is not fully optimized and there is wastage of important chemicals. Optimization will lead to reduction in the wastage, increase the conversion and increase in purity of the compound, and all these factors will lead to driving the cost of production down and in doing so the cost of medicines will also decrease.