Design and Analysis of Single-Bit Ternary Matched Filter

Wireless Personal Communications - Matched filtering has found its way in many diverse applications such as communication, signal processing and more. The emphasis of this paper is on the design...     

Extrusion of highly filled flexible polymer sheet

Highly-filled polymer systems include color masterbatches, feedstocks for powder injection molding, and rigid sheets with high levels of flame retardants, but they have not been explored for flexible sheet. This work investigated the (a) selecting a polymer matrix with enough melt strength and flexibility to form a stable sheet with high filler loading, (b) the maximum achievable filler loading for the sheet, and (c) optimizing the process of extruding a highly-filled flexible polymer system. Extrusion grade low-density polyethylene (LDPE) provided sufficient flexibility and permitted a maximum filler loading of 36 vol% (~78 wt%). Good dispersion of the nanoparticle filler, however, required two passes through multiple screw extruders and a small reduction in the viscosity of the LDPE. Sheet with thickness of 415 μm, surface roughness of <1 μm, and sufficient flexibility was extruded continuously at a rate of 10 m/min., but it required a more traditional coat hanger manifold to prevent filler hang up in the sheet die. The filler particles were distributed uniformly through the core and skin of the sheet, giving the sheet good mechanical properties.     

Impact of adhesive ingredients on adhesion between rubber and brass-plated steel wire in tire

Proficiency on underlying mechanism of rubber-metal adhesion has been increased significantly in the last few decades. Researchers have investigated the effect of various ingredients, such as hexamethoxymethyl melamine, resorcinol, cobalt stearate, and silica, on rubber-metal interface. The role of each ingredient on rubber-metal interfacial adhesion is still a subject of scrutiny. In this article, a typical belt skim compound of truck radial tire is selected and the effect of each adhesive ingredient on adhesion strength is explored. Out of these ingredients, the effect of cobalt stearate is found noteworthy. It has improved adhesion strength by 12% (without aging) and by 11% (humid-aged), respectively, over control compound. For detailed understanding of the effect of cobalt stearate on adhesion, scanning electron microscopy and energy dispersive spectroscopy are utilized to ascertain the rubber coverage and distribution of elements. X-ray photoelectron spectroscopy results helped us to understand the impact of Cu_XS layer depth on rubber-metal adhesion. The depth profile of the Cu_XS layer was found to be one of the dominant factors of rubber-metal adhesion retention. Thus, this study has made an attempt to find the impact of different adhesive ingredients on the formation of Cu_XS layer depth at rubber-metal interface and establish a correlation with adhesion strength simultaneously.     

EMA-PRBDS: efficient multi-attribute packet rank based data scheduling in wireless sensor networks for real-time monitoring systems

ABSTRACT

In recent years, Wireless Sensor Networks (WSNs) are widely placed in real-time monitoring systems like environmental, structural, patient monitoring, etc. The major criterion for WSN includes energy efficiency and network lifetime. Scheduling is used as a large number of data packets focus on the same queue at the same time. Only limited data scheduling schemes have been implemented in WSN to enhance the performance. The existing First Come First Serve (FCFS) and Dynamic Multilevel Priority (DMP) have some technical challenges like delay, packet drop and high energy consumption due to starvation and deadlock. In this paper, we proposed a new algorithm to optimise and rank the incoming data packets based on multi-attributes decision-making methodology named as Packet Rank Based Data Scheduling (PRBDS), the algorithm selects packet priority, deadline, and size as the metrics to rank the incoming data packets. A simulation result shows when compared with existing scheduling, PRBDS not only provides less energy consumption, also significantly reduces the packet drop and increases the lifetime. Thus, the proposed algorithm is most suitable for real-time monitoring system since it combines data ranking method with scheduling algorithm to create accurate and reliable results to evaluate the incoming data packets.     

Photocatalytic degradation of environmental perilous gentian violet dye using leucaena-mediated zinc oxide nanoparticle and its anticancer activity

Phytomediated synthesis of metal oxide nanoparticles has become a key research area in nanotechnology due to its wide applicability in various biomedical fields. The present work explores the biosynthesis of zinc oxide nanoparticles(ZnO-NPs) using Leucaena leucocephala leaf extract. The synthesised ZnO-NPs were characterised by ultraviolet-visible(UV-Vis) spectroscopy, scanning electron microscopy(SEM), energydispersive X-ray spectroscopy(EDX), Fourier transform infrared spectroscopy(FTIR), X-ray diffraction(XRD),transmission electron microscopy(TEM) and selected area electron diffraction(SAED) studies. Biosynthesised ZnONPs are found to have wurtzite hexagonal structure with particles distributed in the range of 50-200 nm as confirmed by TEM studies. The anticancer activity of ZnONPs against MCF-7(breast cancer) and PC-3(human prostate cancer) cell lines was evaluated using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide(MTT) assay. From the assay, biosynthesised ZnO-NPs have better cytotoxic activity on PC-3 cell lines than MCF-7 cell lines. The in vitro cytotoxicity studies of biosynthesised ZnO-NPs against Dalton lymphoma ascites(DLA)cells reveal better antitumor activity of 92% inhibition with concentration of 200 μg·ml~(-1) of ZnO-NPs,and as the concentration increases, the anticancer efficiency as well increases, and also, it has excellent photocatalytic activity to degrade crystal violet dye in aqueous solution after irradiation of 90 min. The result suggests that the green synthesis of ZnO-NPs could be easily recovered and reused several times without any significant loss of the catalytic activity. The advantage of this technique lies in its low cost, easily climb able and non-use of toxic agents.     

Adaptive Buffering and Fuzzy Based Multilevel Clustering for Energy Efficient Wireless Sensor Network

Wireless Personal Communications - Wireless sensor network consists of a number of power constrained sensor nodes that sense data from the environment. The collected data is directed to the base...     

I-CARES: advancing health diagnosis and medication through IoT

Internet of Things (IoT) is changing the way many sectors operate and special attention is paid to promoting healthy living by employing IoT based technologies. In this paper, a novel approach is developed with IoT prototype of Wireless Sensor Network and Cloud based system to provide continuous monitoring of a patient’s health status, ensuring timely scheduled and unscheduled medicinal dosage based on real-time patient vitals measurement, life-saving emergency prediction and communication. The designed integrated prototype consists of a wearable expandable health monitoring system, Smart Medicine Dispensing System, Cloud-based Big Data analytical diagnostic and Artificial Intelligence (AI) based reporting tool. A working prototype was developed and tested on few persons to ensure that it is working according to expected standards. Based on the initial experiments, the system fulfilled intended objectives including continuous health monitoring, scheduled timely medication, unscheduled emergency medication, life-saving emergency reporting, life-saving emergency prediction and early stage diagnosis. In addition, based on the analysis reports, physicians can diagnose/decide, view medication side effects, medication errors and prescribe medication accordingly. The proposed system exhibited the ability to achieve objectives it was designed using IoT to alleviate the pressure on hospitals due to crowdedness in hospital care and to reduce the healthcare service delays.

     

A two stage neural network for choosing optimal ejection parameters in low altitude seat ejection based on novel injury parameter

Optimization and Engineering - Aircraft ejection systems are lifesaving devices used, in case of emergencies for military pilots. As per current literature the success rate of ejections happening...