Solution for intra/inter-cluster event-reporting problem in cluster-based protocols for wireless sensor networks

<span>In recent years, wireless sensor networks (WSNs) have been considered one of the important topics for researchers due to their wide applications in our life. Several researches have been conducted to improve WSNs performance and solve their issues. One of these issues is the energy limitation in WSNs since the source of energy in most WSNs is the battery. Accordingly, various protocols and techniques have been proposed with the intention of reducing power consumption of WSNs and lengthen their lifetime. Cluster-oriented routing protocols are one of the most effective categories of these protocols. In this article, we consider a major issue affecting the performance of this category of protocols, which we call the intra/inter-cluster event-reporting problem (IICERP). We demonstrate that IICERP severely reduces the performance of a cluster-oriented routing protocol, so we suggest an effective Solution for IICERP (SIICERP). To assess SIICERP’s performance, comprehensive simulations were performed to demonstrate the performance of several cluster-oriented protocols without and with SIICERP. Simulation results revealed that SIICERP substantially increases the performance of cluster-oriented routing protocols.</span>

AMROFloor: An Efficient Aging Mitigation and Resource Optimization Floorplanner for Virtual Coarse-Grained Runtime Reconfigurable FPGAs

With the rapid reduction of CMOS process size, the FPGAs with high-silicon accumulation technology are becoming more sensitive to aging effects. This reduces the reliability and service life of the device. The offline aging-aware layout planning based on balance stress is an effective solution. However, the existing methods need to take a long time to solve the floorplanner, and the corresponding layout solutions occupy many on-chip resources. To this end, we proposed an efficient Aging Mitigation and Resource Optimization Floorplanner (AMROFloor) for FPGAs. First, the layout solution is implemented on the Virtual Coarse-Grained Runtime Reconfigurable Architecture, which contributes to avoiding rule constraints for placement and routing. Second, the Maximize Reconfigurable Regions Algorithm (MRRA) is proposed to quickly determine the RRs’ number and size to save the solving time and ensure an effective solution. Furthermore, the Resource Combination Algorithm (RCA) is proposed to optimize the on-chip resources, reducing the on-Chip Resource Utilization (CRU) while achieving the same aging relief effect. Experiments were simulated and implemented on Xilinx FPGA. The results demonstrate that the AMROFloor method designed in this paper can extend the Mean Time to Failure (MTTF) by 13.8% and optimize the resource overhead by 19.2% on average compared to the existing aging-aware layout solutions.

Process Plant Upgradation Using Reliability, Availability, and Maintainability (RAM) Criteria

The objective of this study is to propose a solution for process plant upgradation becoming extinct due to obsoleteness of spares. The study will help in reliability, availability, and maintainability (RAM) based upgradation of control system of process plants in developing countries. Available options for plant upgradation are compact control, modular, and semiautomatic. RAM based upgradation provides solution which is high in reliability and availability (usually all parts are replaced with upgraded and compatible technology) and is easy to maintain throughout the service life of process plant. Case study for stacker and reclaimer of cement plant upgradation is considered to both implement and evaluate the idea. Upgradation methodology is finalized by expert’s feedback regarding selection of hardware with respect to availability, market survey to validate the opinion, and economical availability viability of selected hardware. Pre- and postupgradation scenarios are analyzed to validate the implementation of study and conclude the expected outcomes. The process plant upgradation yielded a cost-effective solution to the problem with automation increasing by 17%, plant maintainability increasing by 80%, and downtime of plant decreasing by 17%. Among all available options, modular design Op1 is considered the best choice that can satisfy RAM criteria.

Scientific journals must be alert to potential manipulation in citations and referencing

Citation is an essential practice in scientific publishing. However, it is mandatory that citing the sources in a scientific work is performed in a proper manner. Manipulating citations in research articles is one form of academic research misconduct that violates publication ethics. Citation manipulation simply occurs for the purpose of increasing the number of citations of a researcher or a journal. Unfortunately, there has been a growing trend for this type of misconduct recently and this has not received much attention from the science community. The most effective solution to prevent the growth of such unethical practices is for reputable journals to impose stricter rules on reference evaluation criteria in order to emphasize on the appropriateness of the citations.

Recombinant HNP-1 Produced by Escherichia coli Triggers Bacterial Apoptosis and Exhibits Antibacterial Activity against Drug-Resistant Bacteria

Human neutrophil peptide-1 (HNP-1) is a promising antibiotic candidate, but its clinical application has been hampered by the difficulty of mass production and an inadequate understanding of its bactericidal mechanisms. In this study, we demonstrated that recombinant protein expression combined with ultrafiltration may be a simple and cost-effective solution to HNP-1 production.

Reinforcement of Protective Coatings Based on Powder Paints with Alumina Nanofibers

The paper deals with the production and study of nanocomposite powder paints based on alumina nanofibers. For nanodispersed fillers, the nature of the surface states on the filler particles is important. The problem of introducing nanomaterials into a polymer matrix cannot provide an effective solution without matching the surface states of the nanomaterial filler and the polymer matrix for the resulting composite materials. The consistency of the surface states of the nanomaterial filler and the polymer matrix determines the quality of transfer of the necessary properties to the resulting polymer composite. In order to increase the affinity of alumina nanofibers with a matrix of powder paint, the nanofibers were treated with 3-glycidyloxypropyltrimethoxysilane (GLYMO) in toluene. It is shown in the work that the addition of alumina nanofibers leads to a hardening of the coating, an increase in its elasticity, and an increase in corrosion resistance. Finishing of alumina nanofibers in a solution of silane in toluene leads to its functionalization, which is sufficient for the distribution of nanofibers in the polymer matrix of the paint and improvement of its operational properties.

PACAM: A Pairwise-Allocated Strategy and Capability Average Matrix-Based Task Scheduling Approach for Edge Computing

With the development of the smart Internet of Things (IoT), an increasing number of tasks are deployed on the edge of the network. Considering the substantially limited processing capability of IoT devices, task scheduling as an effective solution offers low latency and flexible computation to improve the system performance and increase the quality of services. However, limited computing resources make it challenging to assign the right tasks to the right devices at the edge of the network. To this end, we propose a polynomial-time solution, which consists of three steps, i.e., identifying available devices, estimating device quantity, and searching for feasible schedules. In order to shrink the number of potential schedules, we present a pairwise-allocated strategy (PA). Based on these, a capability average matrix (CAM)-based index is designed to further boost efficiency. In addition, we evaluate the schedules by the technique for order preference by similarity to an ideal solution (TOPSIS). Extensive experimental evaluation using both real and synthetic datasets demonstrates the efficiency and effectiveness of our proposed approach.

Deep Reinforcement Learning-Based Workload Scheduling for Edge Computing

Edge computing is a new paradigm for providing cloud computing capacities at the edge of network near mobile users. It offers an effective solution to help mobile devices with computation-intensive and delay-sensitive tasks. However, the edge of network presents a dynamic environment with large number of devices, high mobility of users, heterogeneous applications and intermittent traffic. In such environment, edge computing often suffers from unbalance resource allocation, which leads to task failure and affects system performance. To tackle this problem, we proposed a deep reinforcement learning(DRL)-based workload scheduling approach with the goal of balancing the workload, reducing the service time and the failed task rate. Meanwhile, We adopt Deep-Q-Network(DQN) algorithms to solve the complexity and high dimension of workload scheduling problem. Simulation results show that our proposed approach achieves the best performance in aspects of service time, virtual machine(VM) utilization, and failed tasks rate compared with other approaches. Our DRL-based approach can provide an efficient solution to the workload scheduling problem in edge computing.

Single Stage Active Power Factor Correction Circuit for Street LED Light with Battery Backup

This paper introduces and uses a single-phase, high-power LED driver with a battery backup. The buck–boost converter and reverse converter are both combined to achieve optimal performance. In the first part of the integrated circuit, the buck–boost converter is simply used to adjust the power when operating in the non-continuous operating mode. The reverse converter provides free voltage to the LEDs when released as a remote DC–DC converter. The battery backup cycle directly charges the battery at the same power as the LED driver required and provides charging power when there is no electricity. This paper demonstrates the functionality of the entire system and proves that it is an effective solution for new lighting applications.