Composite autogenous bone and demineralized bone matrix: an effective graft material

Abstract no. 3131published_or_final_versio

For More Energy Efficient Dual-hop DF Relaying Power Line Communication Systems

Energy efficiency in multi-hop cooperative power line communication (PLC) systems has recently received considerable attention in the literature. In order to make such systems more energy-efficient, this paper proposes a relaying technique equipped with energy-harvesting capabilities. More specifically, we consider a dual-hop decode-and-forward (DF) broadband PLC relaying system in which the relay exploits the high noise inherent in PLC channels to further enhance energy efficiency; this system will be referred to as DF with energy-harvesting (DF-EH). This study deploys, particularly, the time-switching relaying protocol for energy-harvesting. An accurate analytical expression for the energy efficiency and a closed-form expression for the average outage probability of the proposed system are derived and then verified with Monte Carlo simulations. For the sake of comparison and to highlight the achievable gains, we also analyze the energy efficiency performances and the average outage probabilities of the conventional DF relaying system, i.e. without energy-harvesting, as well as that of the direct-link approach. Furthermore, various frequency selection and power allocation strategies, namely, optimal frequency selection, random frequency selection and equal power allocation, exploiting the multiple power cables, are studied. Then, the impact of several system parameters such as the energy-harvesting time factor, various idle power consumption profiles, relay location, power allocation as well as different noise scenarios are examined. The results reveal that the proposed DF-EH system is able to provide energy efficiency improvements of more than 30% compared to the conventional DF relaying scheme. It is also shown that the proposed system with optimal frequency selection performs better at low SNR whereas at high SNR the equal power allocation based system will have the best performance

Two-Stage Non-Orthogonal Multiple Access over Power Line Communication Channels

Non-orthogonal multiple access (NOMA) has recently been proposed for dual-hop cooperative relaying power line communication (PLC) systems. Unlike conventional NOMA-PLC schemes which deploy NOMA only at the relay, this paper proposes to enhance the performance of such systems by implementing the principle of NOMA at both the source and relaying modems. The system performance is evaluated in terms of the average sum capacity for which analytical expressions are derived for both the improved and conventional NOMA-PLC systems. Throughout our analysis, the PLC channel is assumed narrow-band modeled with log-normal amplitude distribution and the total PLC noise consists of both background and impulsive noise. Monte Carlo simulations are provided to corroborate the accuracy of our theoretical analysis. The derived expressions are utilized to examine the impact of various system parameters on the average capacity performance; this includes: impulsive noise probability, network branching, power allocation coefficients and transmit power. The optimization problem of the power allocation coefficients is also addressed for both NOMA-PLC systems under consideration. Results reveal that significant gains in the average capacity can be attained with the improved NOMA-PLC approach compared to the conventional system. In addition, the improved system is able to meet a given performance requirement with smaller transmit power offering more relaxed electromagnetic compatibility issues associated with PLCs. Finally, it is demonstrated that optimizing the power allocation coefficients at both the source and relay modems is crucial to maximize performance

IEEE Access Special Section Editorial: Advances in Power Line Communication and its Applications

Power line communication (PLC) is a growing technology which utilizes the existing pre-installed power delivery infrastructure for data transmission. While it is true that the history of PLC technology goes back to the beginning of the last century, when the first data transmission over power lines took place for low data rate control and monitoring purposes, PLC has recently regained a considerable amount of research attention due to the dawn of the internet and the increasing need for fast connectivity. PLC is also expected to serve as a reliable communication medium for many emerging applications of Internet of Things (IoT) and Smart Grids (SGs)

A full privacy-preserving distributed batch-based certificate-less aggregate signature authentication scheme for healthcare wearable wireless medical sensor networks (HWMSNs)

The dynamic connectivity and functionality of sensors has revolutionized remote monitoring applications thanks to the combination of IoT and wireless sensor networks (WSNs). Wearable wireless medical sensor nodes allow continuous monitoring by amassing physiological data, which is very useful in healthcare applications. These text data are then sent to doctors via IoT devices so they can make an accurate diagnosis as soon as possible. However, the transmission of medical text data is extremely vulnerable to security and privacy assaults due to the open nature of the underlying communication medium. Therefore, a certificate-less aggregation-based signature system has been proposed as a solution to the issue by using elliptic curve public key cryptography (ECC) which allows for a highly effective technique. The cost of computing has been reduced by 93% due to the incorporation of aggregation technology. The communication cost is 400 bits which is a significant reduction when compared with its counterparts. The results of the security analysis show that the scheme is robust against forging, tampering, and man-in-the-middle attacks. The primary innovation is that the time required for signature verification can be reduced by using point addition and aggregation. In addition, it does away with the reliance on a centralized medical server in order to do verification. By taking a distributed approach, it is able to fully preserve user privacy, proving its superiority

A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models.

The Internet of Things (IoT) is extensively used in modern-day life, such as in smart homes, intelligent transportation, etc. However, the present security measures cannot fully protect the IoT due to its vulnerability to malicious assaults. Intrusion detection can protect IoT devices from the most harmful attacks as a security tool. Nevertheless, the time and detection efficiencies of conventional intrusion detection methods need to be more accurate. The main contribution of this paper is to develop a simple as well as intelligent security framework for protecting IoT from cyber-attacks. For this purpose, a combination of Decisive Red Fox (DRF) Optimization and Descriptive Back Propagated Radial Basis Function (DBRF) classification are developed in the proposed work. The novelty of this work is, a recently developed DRF optimization methodology incorporated with the machine learning algorithm is utilized for maximizing the security level of IoT systems. First, the data preprocessing and normalization operations are performed to generate the balanced IoT dataset for improving the detection accuracy of classification. Then, the DRF optimization algorithm is applied to optimally tune the features required for accurate intrusion detection and classification. It also supports increasing the training speed and reducing the error rate of the classifier. Moreover, the DBRF classification model is deployed to categorize the normal and attacking data flows using optimized features. Here, the proposed DRF-DBRF security model's performance is validated and tested using five different and popular IoT benchmarking datasets. Finally, the results are compared with the previous anomaly detection approaches by using various evaluation parameters

Regional differences in recombination hotspots between two chicken populations

<p>Abstract</p> <p>Background</p> <p>Although several genetic linkage maps of the chicken genome have been published, the resolution of these maps is limited and does not allow the precise identification of recombination hotspots. The availability of more than 3.2 million SNPs in the chicken genome and the recent advances in high throughput genotyping techniques enabled us to increase marker density for the construction of a high-resolution linkage map of the chicken genome. This high-resolution linkage map allowed us to study recombination hotspots across the genome between two chicken populations: a purebred broiler line and a broiler × broiler cross. In total, 1,619 animals from the two different broiler populations were genotyped with 17,790 SNPs.</p> <p>Results</p> <p>The resulting linkage map comprises 13,340 SNPs. Although 360 polymorphic SNPs that had not been assigned to a known chromosome on chicken genome build WASHUC2 were included in this study, no new linkage groups were found. The resulting linkage map is composed of 31 linkage groups, with a total length of 3,054 cM for the sex-average map of the combined population. The sex-average linkage map of the purebred broiler line is 686 cM smaller than the linkage map of the broiler × broiler cross.</p> <p>Conclusions</p> <p>In this study, we present a linkage map of the chicken genome at a substantially higher resolution than previously published linkage maps. Regional differences in recombination hotspots between the two mapping populations were observed in several chromosomes near the telomere of the p arm; the sex-specific analysis revealed that these regional differences were mainly caused by female-specific recombination hotspots in the broiler × broiler cross.</p