A time-domain approach to the analysis and modeling of on-body propagation characteristics using synchronized measurements at 2.45 GHz

Modeling of on-body propagation channels is of paramount importance to those wishing to evaluate radio channel performance for wearable devices in body area networks (BANs). Difficulties in modeling arise due to the highly variable channel conditions related to changes in the user's state and local environment. This study characterizes these influences by using time-series analysis to examine and model signal characteristics for on-body radio channels in user stationary and mobile scenarios in four different locations: anechoic chamber, open office area, hallway, and outdoor environment. Autocorrelation and cross-correlation functions are reported and shown to be dependent on body state and surroundings. Autoregressive (AR) transfer functions are used to perform time-series analysis and develop models for fading in various on-body links. Due to the non-Gaussian nature of the logarithmically transformed observed signal envelope in the majority of mobile user states, a simple method for reproducing the failing based on lognormal and Nakagami statistics is proposed. The validity of the AR models is evaluated using hypothesis testing, which is based on the Ljung-Box statistic, and the estimated distributional parameters of the simulator output compared with those from experimental results.

Characterization and modeling of on-body spatial diversity within indoor environments at 868 MHz

For the first time in the open literature we present a full characterization of the performance of receiver diversity for the on-body channels found in body area networks. The study involved three commonly encountered diversity combining schemes: selection combination (SC), maximal ratio combining (MRC) and equal gain combining (EGC). Measurements were conducted for both stationary and mobile user scenarios in an anechoic chamber and open office area environment. Achievable diversity gain for various on-body dual branch diversity receivers, consisting of horizontal and vertical spatially separated antennas, was found to be dependent upon transmitter-receive array separation, user state and level of multipath contribution from the local environment. The maximum diversity gain (6.4 dB) was observed for a horizontal two branch MRC combiner while the transmitter and receiver were on opposite sides of the body, and the user was mobile in the open office area. A novel statistical characterization of the fading experienced in on-body diversity channels is also performed using purposely derived first and second order diversity statistics for combiners operating in Nakagami fading.

A Ligand predication tool based on modeling and reasoning with imprecise probabilistic knowledge

Ligand prediction has been driven by a fundamental desire to understand more about how biomolecules recognize their ligands and by the commercial imperative to develop new drugs. Most of the current available software systems are very complex and time-consuming to use. Therefore, developing simple and efficient tools to perform initial screening of interesting compounds is an appealing idea. In this paper, we introduce our tool for very rapid screening for likely ligands (either substrates or inhibitors) based on reasoning with imprecise probabilistic knowledge elicited from past experiments. Probabilistic knowledge is input to the system via a user-friendly interface showing a base compound structure. A prediction of whether a particular compound is a substrate is queried against the acquired probabilistic knowledge base and a probability is returned as an indication of the prediction. This tool will be particularly useful in situations where a number of similar compounds have been screened experimentally, but information is not available for all possible members of that group of compounds. We use two case studies to demonstrate how to use the tool.

Human body shadowing in cellular device-to-device communications: channel modeling using the shadowed κ−μ fading model

Using device-to-device communications as an underlay for cellular communications will provide an exciting opportunity to increase network capacity as well as improving spectral efficiency. The unique geometry of device-to-device links, where user equipment is often held or carried at low elevation and in close proximity to the human body, will mean that they are particularly susceptible to shadowing events caused not only by the local environment but also by the user's body. In this paper, the shadowed κ - μ fading model is proposed, which is capable of characterizing shadowed fading in wireless communication channels. In this model, the statistics of the received signal are manifested by the clustering of multipath components. Within each of these clusters, a dominant signal component with arbitrary power may exist. The resultant dominant signal component, which is formed by the phasor addition of these leading contributions, is assumed to follow a Nakagami- m distribution. The probability density function, moments, and the moment-generating function are also derived. The new model is then applied to device-to-device links operating at 868 MHz in an outdoor urban environment. It was found that shadowing of the resultant dominant component can vary significantly depending upon the position of the user equipment relative to the body and the link geometry. Overall, the shadowed κ - μ fading model is shown to provide a good fit to the field data as well as providing a useful insight into the characteristics of the received signal.

Concrete damage plasticity model for modeling FRP-to-concrete bond behavior

The technique of externally bonding fiber-reinforced polymer (FRP) composites has become very popular worldwide for retrofitting existing reinforced concrete (RC) structures. Debonding of FRP from the concrete substrate is a typical failure mode in such strengthened structures. The bond behavior between FRP and concrete thus plays a crucial role in these structures. The FRP-to-concrete bond behavior has been extensively investigated experimentally, commonly using a single or double shear test of the FRP-to-concrete bonded joint. Comparatively, much less research has been concerned with numerical simulation, chiefly due to difficulties in the accurate modeling of the complex behavior of concrete. This paper presents a simple but robust finite-element (FE) model for simulating the bond behavior in the entire debonding process for the single shear test. A concrete damage plasticity model is proposed to capture the concrete-to-FRP bond behavior. Numerical results are in close agreement with test data, validating the model. In addition to accuracy, the model has two further advantages: it only requires the basic material parameters (i.e., no arbitrary user-defined parameter such as the shear retention factor is required) and it can be directly implemented in the FE software ABAQUS.