Presented paper describes and analyses HARQ (Hybrid Automatic Repeat Request) and pure ARQ schemes. We focus on selected HARQ techniques applied to IP protocol and also to LMS channel. The efficiency of HARQ scheme is compared with GBN schemes using different lengths of IP packets. We show that usage of smaller packets and hybrid schemes leads to an improved throughput. Differences between pure...

Advanced Infrared (AIr) protocol is the Infrared Data Association (IrDA) proposal for indoor optical wireless LANs. AIr utilizes a GoBack-N (GBN) Automatic Repeat Request (ARQ) retransmission scheme at the LC layer to cope with transmission errors. AIr also utilizes Repetition Rate (RR) coding to reach stations with low Signal to Noise Ratios (SNR). This paper studies the effectiveness of repla...

Based on sequence variation in the N-terminus of the UL55 gene, which encodes glycoprotein B (gB), human cytomegalovirus (CMV) can be classified into four gBn genotypes. We assessed the distribution of CMV gBn genotypes and the correlation between CMV gBn DNA (detected by real-time PCR) and CMV-positive pp65 cells (identified by immunohistochemical staining) in a cohort of hematopoietic stem ce...

A Gaussian Bayesian Network (GBN) is a special directed graphical model with conditional Gaussian distributions. It is an efficient statistical tool in the development of decision support systems, because it offers exact algorithms for prediction and inference. Properly, a GBN requires all variables to be defined by a Gaussian prior distribution or by a Gaussian conditional distribution, whose ...

Greiner and Zhou [1] presented ELR, a discriminative parameter-learning algorithm that maximizes conditional likelihood (CL) for a fixed Bayesian Belief Network (BN) structure, and demonstrated that it often produces classifiers that are more accurate than the ones produced using the generative approach (OFE), which finds maximal likelihood parameters. This is especially true when learning para...

The biomedical applications of graphene-based nanomaterials (GBN) have significantly grown in the last years. Many these suppose their intravenous exposure and, this way, GBN could encounter blood cells triggering an immunological response unknown effects. Consequently, understanding relationships between and immune system should be a prerequisite for its adequate use biomedicine. In present st...

In this paper we study the application of Bayesian network models to classify multispectral and hyperspectral remote sensing images. Different models of Bayesian networks as: Naive Bayes (NB), Tree Augmented Naive Bayes (TAN) and General Bayesian Networks (GBN), are applied to the classification of hyperspectral data. In addition, several Bayesian multi-net models: TAN multi-net, GBN multi-net ...

A novel wideband uniplanar electromagnetic bandgap structure with curved line bridges (C-EBG) is proposed to be used in power planes for suppressed ground bounce noise (GBN) and improved signal integrity. Compared with a conventional uniplanar electromagnetic bandgap structure with straight line bridges (S-EBG), the CEBG structure significantly increases the equivalent inductance with less spli...

We propose a new type of ubiquitous decision support system that is powered by a General Bayesian Network (GBN). Because complicated decision support problems are plagued by complexities when interpreting causal relationships among decision variables, GBNs have shown excellent decision support competence because of their flexible structure, which allows them to extract appropriate and robust ca...

Graphene based nanomaterials (GBN) have been recently applied in a broad range of science and technology fields such as nanobiomedicine, electronics, energy storage power generation exploiting their unique electronic structure, physical properties, opportunities for modifying surface using covalent non-covalent interactions. In the present review we systematised origins GBN functionalisation or...