Novel electrospun polymer electrolytes incorporated with Keggin‐type hetero polyoxometalate fillers as solvent‐free electrolytes for lithium ion batteries

In this study, solvent‐free nanofibrous electrolytes were fabricated through an electrospinning method. Polyethylene oxide (PEO), lithium perchlorate and ethylene carbonate were used as polymer matrix, salt and plasticizer respectively in the electrolyte structures. Keggin‐type hetero polyoxometalate (Cu‐POM@Ru‐rGO, Ni‐POM@Ru‐rGO and Co‐POM@Ru‐rGO (POM, polyoxometalate; rGO, reduced graphene oxide)) nanoparticles were synthesized and inserted into the PEO‐based nanofibrous electrolytes. TEM and SEM analyses were carried out for further evaluation of the synthesized filler structures and the electrospun nanofibre morphologies. The fractions of free ions and crystalline phases of the as‐spun electrolytes were estimated by obtaining Fourier transform infrared and XRD spectra, respectively. The results showed a significant improvement in the ionic conductivity of the nanofibrous electrolytes by increasing filler concentrations. The highest ionic conductivity of 0.28 mS cm^?1 was obtained by the introduction of 0.49 wt% Co‐POM@Ru‐rGO into the electrospun electrolyte at ambient temperature. Compared with solution‐cast polymeric electrolytes, the electrospun electrolytes present superior ionic conductivity. Moreover, the cycle stability of the as‐spun electrolytes was clearly improved by the addition of fillers. Furthermore, the mechanical strength was enhanced with the insertion of 0.07 wt% fillers to the electrospun electrolytes. The results implied that the prepared nanofibres are good candidates as solvent‐free electrolytes for lithium ion batteries. © 2020 Society of Chemical Industry     

An incentive scheduling mechanism for peer-to-peer video streaming

P2P video streaming networks are found as a scalable solution and an alternative for traditional client–server based video streaming over the Internet. One of the significant issues affecting the success of any P2P streaming network is cooperation between peers. Practical observations have proved the prevalence of free riders in P2P networks that degrade their performance. To solve this problem, using incentive mechanisms, which encourage peers to contribute more in the network, is necessary. In this paper, we designed and proposed a distributed and scalable incentive mechanism for mesh based P2P video streaming networks. In the proposed approach the contribution of the peers is measured and maintained in a distributed fashion. Furthermore, we proposed an incentive sending side scheduler in which peers are served based on their contribution in the network. Our simulation evaluations show the efficiency of the proposed approach in improving the overall perceived video quality by the non-free rider nodes and consequently in the whole network.     

Multi-objective optimization of a hatchback rear end utilizing fractional factorial design algorithm

Air flow has significant effects on fuel consumption, performance, and comfort. Decreasing drag coefficient enhances fuel consumption and vehicle performance. Moreover, omitting or reducing the power of aerodynamic noise sources provides passengers comfort. In this paper, optimization of a hatchback rear end is conducted considering drag and aerodynamic noise objectives. To this end, five geometrical parameters of the hatchback rear end are chosen as design variables in two levels. Numerical simulation is applied to survey air flow features around the models in the wind tunnel. To reduce the number of runs, fraction factorial design algorithm is applied to generate layout of the simulations which decreased the number of case studies to half. Main and interaction effects of these factors on drag coefficient and acoustic power of the rear end source are derived using analysis of variance. Optimum level for each parameter is chosen considering simultaneous drag and noise goals. Finally, characteristics of air flow and acoustic power around optimum model are discussed.

     

An FEC scheme combined with weighted scheduling to reduce multicast packet loss in IPTV over PON

Congestion is one of the most important challenges in optical networks. In a Passive Optical Network (PON), the Optical Line Terminal (OLT) is a bottleneck and congestion prone. In this paper, a framework is proposed with Forward Error Correction (FEC) at the IP layer combined with Weighted Round Robin (WRR) at the scheduling level to overcome packet-loss due to congestion in the OLT in order to achieve efficient video multicasting over PON. In the FEC scheme, Reed-Solomon (RS(n,k)) with erasure coding is used, where (n−k) erroneous symbols per n symbol blocks can be corrected. In our framework, an Internet Protocol TeleVision (IPTV) service provider uses the mentioned RS coding and generates redundant packets from regular IPTV packets in such a way that an Optical Network Unit (ONU) can recover lost packets from received packets, thus resulting in a better video quality. Simulation results show that using the proposed framework, an ONU can recover many lost packets and achieve better video quality under different traffic loads for its users. For instance, the proposed method can reduce packet loss rate by almost 55% and 10% under traffic load 0.9, respectively, compared with the Round Robin (RR) and WRR methods under symmetric traffic load. When High Receivers Queue (HRQ) traffic (i.e., traffic received by many users) is twice Low Receivers Queue (LRQ) traffic (i.e., traffic received by a small number of users), this reduction is almost 86% and 30% under traffic load 0.9. Finally, when LRQ traffic is twice HRQ traffic, the reduction in packet loss rate is almost 70% and 91% at traffic load 0.5.     

Autocalibration of multiprojector CAVE-like immersive environments

In this paper, we present the first method for the geometric autocalibration of multiple projectors on a set of CAVE-like immersive display surfaces including truncated domes and 4 or 5-wall CAVEs (three side walls, floor, and/or ceiling). All such surfaces can be categorized as swept surfaces and multiple projectors can be registered on them using a single uncalibrated camera without using any physical markers on the surface. Our method can also handle nonlinear distortion in the projectors, common in compact setups where a short throw lens is mounted on each projector. Further, when the whole swept surface is not visible from a single camera view, we can register the projectors using multiple pan and tilted views of the same camera. Thus, our method scales well with different size and resolution of the display. Since we recover the 3D shape of the display, we can achieve registration that is correct from any arbitrary viewpoint appropriate for head-tracked single-user virtual reality systems. We can also achieve wallpapered registration, more appropriate for multiuser collaborative explorations. Though much more immersive than common surfaces like planes and cylinders, general swept surfaces are used today only for niche display environments. Even the more popular 4 or 5-wall CAVE is treated as a piecewise planar surface for calibration purposes and hence projectors are not allowed to be overlapped across the corners. Our method opens up the possibility of using such swept surfaces to create more immersive VR systems without compromising the simplicity of having a completely automatic calibration technique. Such calibration allows completely arbitrary positioning of the projectors in a 5-wall CAVE, without respecting the corners.     

Correction to: Bismuth Yttrium Oxide (Bi3YO6), A New Electrode Material For Asymmetric Aqueous Supercapacitors

Journal of Inorganic and Organometallic Polymers and Materials - The original version of this article unfortunately contained mistakes. In line 9 of the abstract, 5% should read as 2%. The...     

HMM-based state classification of a user with a walking support system using visual PCA features

The improvement of safety and dependability in systems that physically interact with humans requires investigation with respect to the possible states of the user’s motion and an attempt to recognize these states. In this study, we propose a method for real-time visual state classification of a user with a walking support system. The visual features are extracted using principal component analysis and classification is performed by hidden Markov models, both for real-time fall detection (one-class classification) and real-time state recognition (multi-class classification). The algorithms are used in experiments with a passive-type walker robot called “RT Walker” equipped with servo brakes and a depth sensor (Microsoft Kinect). The experiments are performed with 10 subjects, including an experienced physiotherapist who can imitate the walking pattern of the elderly and people with disabilities. The results of the state classification can be used to improve fall-prevention control algorithms for walking support systems. The proposed method can also be used for other vision-based classification applications, which require real-time abnormality detection or state recognition.     

A new intelligent algorithm for dynamic facility layout problem in state of fuzzy constraints

In the present paper, the dynamic facilities layout problem is studied in presence of ambiguity of information flow. Product demand (and consequently material flow) is defined as fuzzy numbers with different membership functions. The problem is modeled in fuzzy programming. Three models of expected value, chance-constrained programming and dependent-chance programming and two hybrid intelligent algorithms are then presented. At the end, efficiency of algorithms for solving fuzzy models of dynamic facilities layout is shown through some numerical examples.