Abstract Wireless Body Area Networks (WBAN) is an emerging type of real-time monitoring used in the healthcare sector. It has the potential to revolutionize the healthcare sector by allowing patients not to physically visit doctor clinics or hospitals for medical checkups. But implementing such a system is challenged by many factors. The most important one is energy consumption. Energy consumption of... Wireless Body Area Networks (WBAN) is an emerging type of real-time monitoring used in the healthcare sector. It has the potential to revolutionize the healthcare sector by allowing patients not to physically visit doctor clinics or hospitals for medical checkups. But implementing such a system is challenged by many factors. The most important one is energy consumption. Energy consumption of all nodes in general and that of the gateway node in particular is critical. The gateway node is responsible for conveying sensor information to medical servers or doctors. Failure of the gateway node means failure of the overall WBAN system of a patient. Thus, extending the life time of the gateway node is a desirable objective in designing WBAN systems. As energy consumption is directly related to the end-to-end delay, Packet Delivery Ratio (PDR) and medium accessibility rate. So, placement on the human body in a location that is affected the least by delay and has high PDR and medium accessibility should be chosen as the placement location for the gateway node. In this paper, we identify the optimal placement location on the human body for a gateway node in terms of end-to-end delay, PDR, and back-off duration period. Read More Read Less

Abstract The purpose of this paper is to define the best training algorithm and activation function during the training process of a two degree of freedom planar robot arm that can be used to approach SCARA applications. A feed-forward neural network with two hidden layers was trained with several training algorithms such as Levenberg-Marquardt, Bayesian Regularization and others, and the activation... The purpose of this paper is to define the best training algorithm and activation function during the training process of a two degree of freedom planar robot arm that can be used to approach SCARA applications. A feed-forward neural network with two hidden layers was trained with several training algorithms such as Levenberg-Marquardt, Bayesian Regularization and others, and the activation functions such as symmetric sigmoid, logarithmic sigmoid and linear transfer to compare the resulting error and look for optimal performance. Read More Read Less

Abstract Protocols of collect and dissemination have been attracting great interest from research community. Our paper identifies the motivation and challenges for applying an opportunistic collect and dissemination of information in urban environment with this state of the art. Also, we consider that there is an important difference between the approach of collect / dissemination and routing of data, which... Protocols of collect and dissemination have been attracting great interest from research community. Our paper identifies the motivation and challenges for applying an opportunistic collect and dissemination of information in urban environment with this state of the art. Also, we consider that there is an important difference between the approach of collect / dissemination and routing of data, which we aim to highlight, subsequently, we study the scientific community classification and describe our classifications. Read More Read Less