Circuit model for diffuse multipath and electromagnetic absorption prediction in rooms

We present a room electromagnetics-based theory which primarily models the diffuse multipath components (DMC) power density with a simple circuit model, and afterwards includes the line-of-sight (LOS) component to predict the total exposure in a realistic environment. Given a human absorption cross section (ACS) and its location from a transmitter (Tx), the average whole-body specific absorption rate (SAR(wb)) can be determined by the proposed circuit model for ultra-wideband (UWB) and wireless local area network (WLAN) systems. The SAR(wb) in humans in a realistic office environment for both UWB and WLAN systems is investigated as part of application. The theory is simulated with the Advanced Design System (ADS) software, and excellent agreement between theoretical and simulated values are obtained in terms of relative errors (<2%). The model may be very useful for SAR(wb) prediction in realistic complex indoor environments

Connectivity Influences on Nonlinear Dynamics in Weakly-Synchronized Networks: Insights from Rössler Systems, Electronic Chaotic Oscillators, Model and Biological Neurons

Natural and engineered networks, such as interconnected neurons, ecological and social networks, coupled oscillators, wireless terminals and power loads, are characterized by an appreciable heterogeneity in the local connectivity around each node. For instance, in both elementary structures such as stars and complex graphs having scale-free topology, a minority of elements are linked to the rest of the network disproportionately strongly. While the effect of the arrangement of structural connections on the emergent synchronization pattern has been studied extensively, considerably less is known about its influence on the temporal dynamics unfolding within each node. Here, we present a comprehensive investigation across diverse simulated and experimental systems, encompassing star and complex networks of Rössler systems, coupled hysteresis-based electronic oscillators, microcircuits of leaky integrate-and-fire model neurons, and finally recordings from in-vitro cultures of spontaneously-growing neuronal networks. We systematically consider a range of dynamical measures, including the correlation dimension, nonlinear prediction error, permutation entropy, and other information-theoretical indices. The empirical evidence gathered reveals that under situations of weak synchronization, wherein rather than a collective behavior one observes significantly differentiated dynamics, denser connectivity tends to locally promote the emergence of stronger signatures of nonlinear dynamics. In deterministic systems, transition to chaos and generation of higher-dimensional signals were observed; however, when the coupling is stronger, this relationship may be lost or even inverted. In systems with a strong stochastic component, the generation of more temporally-organized activity could be induced. These observations have many potential implications across diverse fields of basic and applied science, for example, in the design of distributed sensing systems based on wireless coupled oscillators, in network identification and control, as well as in the interpretation of neuroscientific and other dynamical data

Model Based System Design for Electric Vehicle Conversion

Development of electric vehicle (EV) conversion process can be implemented in a low-cost and time-saving manner, along with the design of actual components. Model-based system design is employed to systematically compute the power flow of the electric vehicle propulsion and dynamic load. Vehicle specification and driving cycles were the two main inputs for the simulation. As a result, the approach is capable of predicting various EV characteristics and design parameters, such as EV performance, driving range, torque speed characteristics, motor power, and battery power charge/discharge, which are the necessity for the design and sizing selection of the main EV components. Furthermore, drive-by-wire (DBW) ECU function can be employed by means of model-based design to improve drivability. For the current setup, the system components are consisted of actual ECU hardware, electric vehicle models, and control area network (CAN) communication. The EV component and system models are virtually simulated simultaneously in real time. Thus, the EV functionalities are verified corresponding to objective requirements. The current methodology can be employed as rapid design tool for ECU and software development. Same methodology can be illustrated to be used for EV tuning and reliability model test in the future

MGSim - Simulation tools for multi-core processor architectures

MGSim is an open source discrete event simulator for on-chip hardware components, developed at the University of Amsterdam. It is intended to be a research and teaching vehicle to study the fine-grained hardware/software interactions on many-core and hardware multithreaded processors. It includes support for core models with different instruction sets, a configurable multi-core interconnect, multiple configurable cache and memory models, a dedicated I/O subsystem, and comprehensive monitoring and interaction facilities. The default model configuration shipped with MGSim implements Microgrids, a many-core architecture with hardware concurrency management. MGSim is furthermore written mostly in C++ and uses object classes to represent chip components. It is optimized for architecture models that can be described as process networks.Comment: 33 pages, 22 figures, 4 listings, 2 table