Unified performance analysis over Mckay–Meijer G shadowed fading channel

ABSTRACT

Composite fading models have been considered as the suitable fading models for scenarios such as indoor communication and free space optical. Most of the composite fading models are based on Nakagami-m fading distribution in which amount of fading parameter ranges from 0.5 (most severe fading) to infinity (no fading). However, using the McKay–Meijer G function, one of the recent article presents McKay shadowed fading distribution which shows that the fading severity may have values more than that of the most severe case of Nakagami-m fading. In this paper, using the conditional unified expression for conditional bit error rate (BER), a unified expression of the average bit error rate (ABER) over McKay–Meijer G shadowed fading model has been proposed. The proposed unified expression includes the ABER of almost all the modulation schemes. In addition, expression for ABER of binary phase shift keying modulation over McKay fading channel under generalised Gaussian distribution has been derived. Finally, analytical expressions of adaptive capacity under different adaptive schemes namely, COPRA, CORA, CCIFR and truncated CIFR have been presented. Through numerical analysis, different results have been compared with similar results available in the literature.     

Evolutionary non‐cooperative spectrum sharing game: long‐term coexistence for collocated cognitive radio networks

Collocated cognitive radio networks (CRNs) employ coexistence protocols to share the spectrum when it is not being used by the licensed primary users. These protocols work under the assumption that all spectrum bands provide the same level of quality of service, which is somewhat simplistic because channel conditions as well as the licensee's usage of allocated channels can vary significantly with time and space. These circumstances dictate that some channels may be considered better than others; therefore, CRNs are expected to have a preference over the choice of available channels. Because all CRNs are assumed to be rational and select the best available channels, it can lead to an imbalance in contention for disparate channels, degraded quality of service, and an overall inefficient utilization of spectrum resource. In this paper, we analyze this situation from a game theoretic perspective and model the coexistence of CRNs with heterogeneous spectrum as an evolutionary anti‐coordination spectrum‐sharing game. We derive the evolutionarily stable strategy (ESS) of the game by proving that it cannot be invaded by a greedy strategy. We also derive the replicator dynamics of the proposed evolutionary game, a mechanism with which players can learn from their payoff outcomes of strategic interactions and modify their strategies at every stage of the game and subsequently converge to ESS. Because all CRNs approach ESS based solely upon the common knowledge payoff observations, the evolutionary game can be implemented in a distributed manner. Finally, we analyze the game from the perspective of fairness using Jain's fairness index under selfish behavior from CRNs. Copyright © 2016 John Wiley & Sons, Ltd.     

Performance analysis of motion-compensated de-interlacing systems.

A lot of research has been conducted on motion-compensated (MC) de-interlacing, but there are very few publications that discuss the performances of de-interlacing quantatively. The various methods are compared through their performance on known video sequences. Linear system analysis of interlaced video and de-interlacer are proposed in. It is well established that the performance of the MC methods outperform the fixed or motion-adaptive methods when the motion vectors used are reliable and true to the scene content. Being an open-loop process the performance of the MC de-interlacers degrade drastically when there are motion vector errors. In this paper, a linear system analysis of MC video upconversion systems is presented and the effects of motion vector accuracy on system performance are analyzed. We investigate the various factors that contribute to the motion vector inaccuracy, such as incorrect motion modelling, acceleration between the frames, and insufficient interpolation kernel.     

Support Vector Machine (SVM) based compression artifact‐reduction technique

Abstract— A compression artifact‐reduction algorithm based on support vector regression is proposed. The algorithm belongs to a broad family of standard reconstruction methods, but a standardization model is determined from a set of training samples of original images and the corresponding noise‐corrupted version. As opposed to artifact‐reduction methods specific to each type of compression artifact (e.g., blocking, ringing, etc.), we treat such artifacts as a manifestation of the same problem, which is the quantization of DCT coefficients. In the testing step, the algorithm tries to undo the effect of quantization by using the relationship between the original and artifact‐corrupted image, determined during the training step. Experimental results exhibit significant reduction in all types of compression artifacts.     

Room-temperature H2S gas sensing at ppb level by single crystal In2O3 whiskers

In₂O₃ whiskers and bipyramidal nano-crystals were prepared by a carbothermal method. These were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy dispersive X-ray analysis (EDX), photoluminescence and Raman spectroscopy. These were studied for application to sensing of H₂S gas. The single crystal whiskers were found to be sensitive to as low as 200 ppb of H₂S gas at room temperature and showed saturation in response at 10 ppm. On the other hand, the films made of bipyramids were less sensitive to H₂S gas and the response was found to be a nearly linear function of concentration in a concentration range of 10–80 ppm.     

Mycobacterium tuberculosis Acetyltransferase Suppresses Oxidative Stress by Inducing Peroxisome Formation in Macrophages

Mycobacterium tuberculosis (Mtb) inhibits host oxidative stress responses facilitating its survival in macrophages; however, the underlying molecular mechanisms are poorly understood. Here, we identified a Mtb acetyltransferase (Rv3034c) as a novel counter actor of macrophage oxidative stress responses by inducing peroxisome formation. An inducible Rv3034c deletion mutant of Mtb failed to induce peroxisome biogenesis, expression of the peroxisomal β-oxidation pathway intermediates (ACOX1, ACAA1, MFP2) in macrophages, resulting in reduced intracellular survival compared to the parental strain. This reduced virulence phenotype was rescued by repletion of Rv3034c. Peroxisome induction depended on the interaction between Rv3034c and the macrophage mannose receptor (MR). Interaction between Rv3034c and MR induced expression of the peroxisomal biogenesis proteins PEX5p, PEX13p, PEX14p, PEX11β, PEX19p, the peroxisomal membrane lipid transporter ABCD3, and catalase. Expression of PEX14p and ABCD3 was also enhanced in lungs from Mtb aerosol-infected mice. This is the first report that peroxisome-mediated control of ROS balance is essential for innate immune responses to Mtb but can be counteracted by the mycobacterial acetyltransferase Rv3034c. Thus, peroxisomes represent interesting targets for host-directed therapeutics to tuberculosis.     

Microstructural investigations on simulated intercritical heat-affected zone of boron modified P91-steel

Conventional P91 and boron modified P91-steels were considered in the present investigation. Using Gleeble, weld intercritical heat-affected zone (ICHAZ) was processed. Conventional microscopy was done along with electron back-scattered diffraction for both specimens. Lath boundary of martensite was more, and preferably oriented for P91B-ICHAZ than P91-ICHAZ. Lattice strain was high and lath mobility was low for P91B-ICHAZ in comparison to P91-ICHAZ. Large fraction of ferritic grain structure (39.1%) and small fraction of fresh martensitic grain structure (9.5%) in P91-ICHAZ, whereas small fraction of ferritic grain structure (10.7%) and large fraction of fresh martensitic grain structure (32.7%) in P91B-ICHAZ was observed. However, tempered martensite exhibited meager variation. These differences between ICHAZ simulations were attributed to the presence of 100ppm-boron in P91B-steel.     

Bayesian Rule Modeling for Interpretable Mortality Classification of COVID-19 Patients

Coronavirus disease 2019 (COVID-19) has been termed a “Pandemic Disease” that has infected many people and caused many deaths on a nearly unprecedented level. As more people are infected each day, it continues to pose a serious threat to humanity worldwide. As a result, healthcare systems around the world are facing a shortage of medical space such as wards and sickbeds. In most cases, healthy people experience tolerable symptoms if they are infected. However, in other cases, patients may suffer severe symptoms and require treatment in an intensive care unit. Thus, hospitals should select patients who have a high risk of death and treat them first. To solve this problem, a number of models have been developed for mortality prediction. However, they lack interpretability and generalization. To prepare a model that addresses these issues, we proposed a COVID-19 mortality prediction model that could provide new insights. We identified blood factors that could affect the prediction of COVID-19 mortality. In particular, we focused on dependency reduction using partial correlation and mutual information. Next, we used the Class-Attribute Interdependency Maximization (CAIM) algorithm to bin continuous values. Then, we used Jensen Shannon Divergence (JSD) and Bayesian posterior probability to create less redundant and more accurate rules. We provided a ruleset with its own posterior probability as a result. The extracted rules are in the form of “if antecedent then results, posterior probability()”. If the sample matches the extracted rules, then the result is positive. The average AUC Score was 96.77% for the validation dataset and the F1-score was 92.8% for the test data. Compared to the results of previous studies, it shows good performance in terms of classification performance, generalization, and interpretability.