Radar target tracking via robust linear filtering

In this letter, we provide a robust version of a linear Kalman filter for target tracking based on a measurement conversion technique on the nonlinear radar measurements. We prove that the state estimation error is bounded in a probabilistic sense. We compare our approach with the current state of the art in converted radar measurement-based linear filtering.

Target tracking with range and bearing measurements via robust linear filtering

In this paper we provide a robust version of a linear Kalman filter for target tracking with nonlinear range and bearing measurements. Moreover, we prove that the state estimation error is bounded in a probabilistic sense. We compare our approach with the current state of the art in converted radar measurement based linear filtering.

Conceptualizing women's sexual function : linear vs. circular models of sexual response

Introduction. The lack of an adequate empirical base for models of female sexual response is a critical issue within the female sexual dysfunction (FSD) literature.

Aim. The current research compared the extent to which a linear model of sexual response and Basson's circular model of female sexual response represent the sexual function of women with and without FSD.

Main Outcome Measures. Women's levels of sexual function/dysfunction were assessed with the Female Sexual Function Index and additional items measured women's endorsement of models of female sexual function as representing their own sexual experience.

Methods. An anonymous online survey assessing female sexual response and associated aetiological factors was completed by a random sample of 404 women.

Results. Although the linear model of sexual response was a good fit for women with and without sexual dysfunction, the relationship between sexual arousal and orgasm was mediated by sexual desire for women with FSD. The fit of the initial circular model of women's sexual response was poor for both groups. Following pathway modification, the modified circular model adequately represented the responses of both groups and revealed that a number of the relationships between sexual response variables were stronger for women with FSD.

Conclusions. The linear model was a more accurate representation of sexual response for women with normal sexual function than women with FSD and sexual arousal and orgasm was mediated by sexual desire for women with FSD. The modified circular model was a more accurate representation of the sexual response of women with FSD than women with normal sexual function.

Radiation exposure and the justification of computed tomography scanning in an Australian hospital emergency department

In an emergency department (ED), computed tomography (CT) is particularly beneficial in the investigation of high-speed trauma patients. With the advent of multidetector CT (MDCT) scanners, it is becoming faster and easier to conduct scans. In recent years, this has become evident with an increasing number of CT requests. Patients who have multiple CT scans during their hospital stay can receive radiation doses that have an increased theoretical risk of induction of cancer. It is essential that the clinical justification for each CT scan be considered on an individual basis and that due consideration is given to the radiation risk and possible diagnostic benefit. The current lack of a central State or Commonwealth data repository for medical images is a contributing factor to excessive radiation dosage to the population. The principles of justification and radiation risks are discussed in this study.

Highly linear low voltage low power CMOS LNA

A highly linear, low voltage, low power, low noise amplifier (LNA) using a novel nonlinearity cancellation technique is presented in this paper. Parallel Inductor (PI) matching is used to increase LNA gain by 3dB at the desired frequency. The linear LNA was designed and simulated in a TSMC 0.18μm CMOS process at 5GHz frequency. By employing the proposed technique, the IIP3 is improved by 12dB in contrast to the conventional folded cascode LNA, reaching −1dBm without having any significant effect on the other LNA parameters such as gain, NF and also power consumption. The proposed LNA also delivers a voltage gain (S21) of 12.25dB with a noise figure of 3.5dB, while consuming only 1.28mW of DC power with a low supply voltage of 0.6V.

An improved stability criterion for time-delay power systems with electric vehicles and high voltage direct current power links

This paper presents an improved stability criterion for load frequency control (LFC) of time-delay power systems including AC/HVDC transmission links and EVs. By employing a novel refined Jensen-based inequality, an improved stability condition is derived in terms of feasible linear matrix inequalities (LMIs) which allow us to compute the maximal upper bounds of time-delay ensuring stability of the LFC scheme equipped with an embedded controller. Cases studies here are implemented for LFC scheme of a two-area power system, which is interconnected by parallel (AC/HVDC) links, with embedded proportional integral (PI) controller for discharged EVs. The relationships between the parameters of PI controller, supplementary control of HVDC links and delay margins of the LFC scheme are also discussed. As a consequence of facts, the results of delay margins can be used as a guideline to tune PI controller and set-up parameters for HVDC control.

Effects of increasing neuromuscular electrical stimulation current intensity on cortical sensorimotor network activation: a time domain fNIRS study

Neuroimaging studies have shown neuromuscular electrical stimulation (NMES)-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and secondary somatosensory area (S2), as well as regions of the prefrontal cortex (PFC) known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI), and with reference to voluntary (VOL) wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin concentrations were estimated. The O2Hb and HHb maps obtained using the General Linear Model (NIRS-SPM) analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O2Hb and corresponding decrease in HHb) in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2). However, the level and area of contralateral sensorimotor network (including PFC) activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions.

A fast malware feature selection approach using a hybrid of multi-linear and stepwise binary logistic regression

Malware replicates itself and produces offspring with the same characteristics but different signatures by using code obfuscation techniques. Current generation anti-virus engines employ a signature-template type detection approach where malware can easily evade existing signatures in the database. This reduces the capability of current anti-virus engines in detecting malware. In this paper, we propose a stepwise binary logistic regression-based dimensionality reduction techniques for malware detection using application program interface (API) call statistics. Finding the most significant malware feature using traditional wrapper-based approaches takes an exponential complexity of the dimension (m) of the dataset with a brute-force search strategies and order of (m-1) complexity with a backward elimination filter heuristics. The novelty of the proposed approach is that it finds the worst case computational complexity which is less than order of (m-1). The proposed approach uses multi-linear regression and the p-value of each individual API feature for selection of the most uncorrelated and significant features in order to reduce the dimensionality of the large malware data and to ensure the absence of multi-collinearity. The stepwise logistic regression approach is then employed to test the significance of the individual malware feature based on their corresponding Wald statistic and to construct the binary decision the model. When the selected most significant APIs are used in a decision rule generation systems, this approach not only reduces the tree size but also improves classification performance. Exhaustive experiments on a large malware data set show that the proposed approach clearly exceeds the existing standard decision rule, support vector machine-based template approach with complete data and provides a better statistical fitness.