Improved transmit steering for MIMO-OFDM downlinks with distributed base station antenna arrays

Space-division multiple-access (SDMA) is a communication technique that enables a base station to communicate with several mobile users simultaneously. The ability of the base station to spatially separate several users depends on the pairwise cross correlations between the channel matrices of the users (the inter-user correlation). In this paper, we propose an improved steering downlink multiple-input-multiple-output-orthogonal frequency-division multiplexing (OFDM) system that reduces both the inter-user correlation and the near-far problem resulting in a significant enhancement in system performance. In this system, several base station multiantenna arrays are distributed in a given area. Each array communicates with the base station via optical fiber links, and all transmitter signal processing is performed at the base station. Multiantenna users are spatially separated such that only a subset of the users is served by each tone of the OFDM symbol. The served users are selected based on an algorithm that reduces the inter-user correlations. Distributing the arrays around the users also balances the channel matrix leading to significant reduction in the effect of the near-far problem. The channel matrix of each user is assumed correlated and Ricean distributed. Several data symbols can be spatially multiplexed to each user over each OFDM tone with high reliability and with good total system capacity.     

An optimal deep learning framework for multi-type hemorrhagic lesions detection and quantification in head CT images for traumatic brain injury

Applied Intelligence - Traumatic Brain Injury (TBI) could lead to intracranial hemorrhage (ICH), which has now been identified as a major cause of death after trauma if it is not adequately...     

Current Concepts on Genetic Aspects of Mitochondrial Dysfunction in Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS), neurodegenerative motor neuron disorder is characterized as multisystem disease with important contribution of genetic factors. The etiopahogenesis of ALS is not fully elucidate, but the dominant theory at present relates to RNA processing, as well as protein aggregation and miss-folding, oxidative stress, glutamate excitotoxicity, inflammation and epigenetic dysregulation. Additionally, as mitochondria plays a leading role in cellular homeostasis maintenance, a rising amount of evidence indicates mitochondrial dysfunction as a substantial contributor to disease onset and progression. The aim of this review is to summarize most relevant findings that link genetic factors in ALS pathogenesis with different mechanisms with mitochondrial involvement (respiratory chain, OXPHOS control, calcium buffering, axonal transport, inflammation, mitophagy, etc.). We highlight the importance of a widening perspective for better understanding overlapping pathophysiological pathways in ALS and neurodegeneration in general. Finally, current and potentially novel therapies, especially gene specific therapies, targeting mitochondrial dysfunction are discussed briefly.     

Acute asthma: treatment and outcome of 2000 consecutive pediatric emergency room visits in Doha, Qatar

Caring for a "difficult patient" is a concern frequently communicated among nurses and reported in the clinical and research literature. A theoretical perspective explaining the phenomenon of difficult patients is proposed and is based on a reformulation of propositions from labeling theory and the concept of social deviance. Applications to nursing practice focus on patient characteristics judged as deviant by nurses, communication of the deviant label, and exclusionary and inclusionary reactions to perceived patient deviance.     

Enhancing the performance of the EWMA control chart for monitoring the process mean using auxiliary information

When using control charts to monitor manufacturing processes, the exponentially weighted moving average (EWMA) control chart is useful for detecting persistent shifts in the process parameter. This paper proposes enhancements to the applications of the EWMA control chart for those scenarios where the exact measurement of process units is difficult and expensive, but the visual ordering of the units can be done easily. The proposed charts use an auxiliary variable that is correlated with the process variable to provide efficient monitoring of shifts in the process mean and are formulated based on ranked set sampling (RSS) and median RSS schemes (MRSS). Simulation results showed that the proposed charting schemes are more efficient in detecting a shift in the process mean than the classical EWMA control chart and its modification. An example is provided to show the application of the proposed charts using a simulated benchmark process: the continuous stirred tank reactor (CSTR).     

On the performance of coefficient of variation control charts in Phase I

Control charts are mainly carried out in 2 interconnected phases: Phase I (retrospective phase) and Phase II (monitoring phase). Phase I uses a stable historical sample to establish control limits that will be used later in Phase II. The preciseness of the control limits obtained from Phase I can greatly affect the performance of control charts in Phase II. Monitoring the coefficient of variation (CV) is an effective approach when the process mean or standard deviation is not constant. Until now, little work has been dedicated on investigating the performance of CV control charts in Phase I. Viewed under this perspective, this study investigates the performance of CV control charts in Phase I in terms of probability to signal. A real‐life example is also provided to illustrate the working of CV charts in Phase I.     

On Model Selection for Autocorrelated Processes in Statistical Process Control

Using traditional control charts to monitor autocorrelated processes is not beneficial, because it will lead us to misleading detections in the processes. One of the methods used to deal with the control charts for autocorrelated process is the model‐based approach. It uses an adequate time series model that fits the process and uses the residuals as monitoring statistics. For the said purpose, it is important to pick a suitable model that can adequately be used for different designs of control charts under specific time series model. This study intends to do the same for three popular types of charts namely Shewhart, exponentially weighted moving average, and cumulative sum. The models covered in this study include AR(1), MA(1), and ARMA(1,1) as the potential models to fit the process of interest. We have focused on two performance aspects namely efficiency and robustness. Average run length is used as a performance measure for different in‐control and out‐of‐control states of the autocorrelated processes under varying levels of autocorrelation. An application example based on a real data set is also included in the study to highlight the importance of the study proposals. Copyright © 2016 John Wiley & Sons, Ltd.