Cedrus oil—A promising storage fungitoxicant

Seeds of two spices Coriandrum sativum and Foeniculum vulgare, were dressed separately with essential oil of Cedrus deodara as well as with five synthetic fungicides viz., phenylmercury acetate, 2-methoxyethyl mercury chloride, copper oxychloride, mancozeb and wettable sulphur. Treated seeds were stored in polythene bags for 12 months. On mycofloral analysis, the oil had checked the appearance of ten fungi, Absidia sp., Alternaria alternata, Aspergillus flavus, A. fumigatus, A. niger, A. ruber, A. versicolor, Cladosporium cladosporioides, Curvularia lunata, and Paecilomyces variotii on the seeds of C. sativum, and seven fungi, Absidia sp., A. flavus, A. fumigatus, A. niger, A. ruber, A. versicolor, and Rhizopus spp., on the seeds of F. vulgare. The oil proved to be more effective than the synthetic fungicides. Further, the oil did not show any adverse effect on seed germination and seedling growth of both spices.     

A novel delay-aware routing algorithm (DARA) for a hybrid wireless-optical broadband access network (WOBAN)

A hybrid wireless-optical broadband access network (WOBAN) is a promising architecture for future access networks. Recently, the WOBAN has been gaining increasing attention, and early versions are being deployed as municipal access solutions. This architecture saves on network deployment cost because fiber need not penetrate to each end user. However, a major research opportunity exists in developing an efficient routing algorithm for the wireless front-end of the WOBAN. We propose and investigate the characteristics of the delay-aware routing algorithm (DARA) that minimizes the average packet delay in the wireless front-end of a WOBAN. In DARA we model wireless routers as queues and predict wireless link states periodically. Our performance studies show that DARA achieves less delay and congestion, and improved load balancing compared to traditional approaches such as the minimum-hop routing algorithm, shortest-path routing algorithm, and predictive throughput routing algorithm.     

Gain Enhancement of Antipodal Vivaldi Antenna for 5G Applications Using Metamaterial

The proposed system portrays the application space examination of a diverse cryptosystem processor with dynamic reconfiguration abilities. It is appropriate to a variety of signal processing application domains namely telecommunications, image processing, video coding and cryptographic processing. To differentiate between application spaces of the processor, the performance is correlated with cutting edge devices, taking ability to program, energy efficiency and computational potential as the important factors. In general the conventional method of computation is processed by means of Virtual Secure Circuit (VSC) on Advanced Encryption Standard (AES) and performance of the device Field Programmable Gate Array (FPGA) after implementation is analyzed in terms of delay and throughput. In the conventional method area overhead and power consumption are less where as the architecture lags in performance and throughput. It has been overcome through the fully parallel pipelined Architecture of the VSC on AES which outperforms the existing method in terms of performance and throughput. The energy efficiency and performance are considerably more important than processor that are used for general purpose, while still preserving a Convenient approach of programming that mainly bank on software oriented languages. The exploit of VSC based AES is to formulate the cryptographic processor held against Side Channel Attacks like attacks based on power supply and electromagnetic signals. Then the experimental result shows the promising outcomes when compared to previous methods.

     

Image quality assessment of modified adaptable VQ used in DCT based image compression schemes implemented on DSP and FPGA platforms

Multimedia Tools and Applications - The world of electronics in particularly in the field of image processing, numerous distinguishable and noteworthy contributions have been made available....     

Nature inspired supply chain solutions: definitions,analogies, and future research directions

ABSTRACT

Supply chains are becoming increasingly complex, and many companies and researchers are looking to nature for finding solutions. In this paper, we provide a narrative synthesis and systematic review to explore state-of-the-art, and identify key areas for exploration of nature inspired solutions in the supply chain area. We consider strategic, tactical, and operational decisions within supply chains and identify analogies between biological systems and supply chains to create a new research agenda. Our findings show that the majority of the research in nature inspired supply chains from the systemic perspective focuses on closed loop supply chains. In contrast, similar systemic solutions such as industrial symbiosis, circular economy, and industrial ecology have not been explored as frequently. Reducing production waste (industrial symbiosis) in addition to end-of-life product waste (closed loop supply chains), optimising raw material use and extending the life of used resources (circular economy), investigating the interactions between biosphere and technosphere (industrial ecology), and seeking solutions to industrial problems from nature (biomimicry) are all possible paths for reaching a zero-waste economy. These systemic solutions have a considerable impact on the supply chains at the strategic, tactical, and operational levels, which need to be explored to identify efficient and effective solutions.     

The application of a radial basis function neural network for predicting the surface roughness in a turning process

This study considers the performance of a radial basis function neural network for predicting the surface roughness in a turning process. A simple algorithm is proposed for finding the upper and lower estimates of the surface roughness. A code is developed that automatically fits the best network architecture for a given training and testing dataset. The validation of the methodology is carried out for dry and wet turning of mild steel using HSS and carbide tools, and is compared to the performance of the studied network with the reported performance of a multi-layer perception neural network. It is observed that the performance of the radial basis function network is slightly inferior compared to multi-layer perceptron neural network. However, the training procedure is simpler and requires less computational time.     

A stochastic approximation approach to active queue management

Recently, a dynamic adaptive queue management with random dropping (AQMRD) scheme has been developed to capture the time-dependent variation of average queue size by incorporating the rate of change of average queue size as a parameter. A major issue with AQMRD is the choice of parameters. In this paper, a novel online stochastic approximation based optimization scheme is proposed to dynamically tune the parameters of AQMRD and which is also applicable for other active queue management (AQM) algorithms. Our optimization scheme significantly improves the throughput, average queue size, and loss-rate in relation to other AQM schemes.     

Optical backbone and control of attocell network

Photonic Network Communications - For serving futuristic applications like distributed robotic systems with robots equipped with humanoid intelligence, wireless access to high-performance computing...     

Epitope‐Resolved Detection of Peanut‐Specific IgE Antibodies by Surface Plasmon Resonance Imaging

Peanut allergy can be life‐threatening and is mediated by allergen‐specific immunoglobulin E (IgE) antibodies. Investigation of IgE antibody binding to allergenic epitopes can identify specific interactions underlying the allergic response. Here, we report a surface plasmon resonance imaging (SPRi) immunoassay for differentiating IgE antibodies by epitope‐resolved detection. IgE antibodies were first captured by magnetic beads bearing IgE ?‐chain‐specific antibodies and then introduced into an SPRi array immobilized with epitopes from the major peanut allergen glycoprotein Arachis hypogaea h2 (Ara h2). Differential epitope responses were achieved by establishing a binding environment that minimized cross‐reactivity while maximizing analytical sensitivity. IgE antibody binding to each Ara h2 epitope was distinguished and quantified from patient serum samples (10 μL each) in a 45 min assay. Excellent correlation of Ara h2‐specific IgE values was found between ImmunoCAP assays and the new SPRi method.     

Enhancement in electrical and magnetodielectric properties of Ca‐ and Ba‐doped BiFeO3 polycrystalline ceramics

We carried out a comparative study on the electrical and magnetodielectric properties of polycrystalline BiFeO₃, Bi_0.9Ca_0.1FeO_2.95, Bi_0.9Ba_0.05Ca_0.05FeO_2.95, and Bi_0.9Ba_0.1FeO_2.95 ceramics. The two dielectric anomalies, near 25 K and 281 K, are observed for BiFeO₃. Interestingly, the anomaly near 25 K shifts towards a higher temperature above 60 K with Ca and/or Ba doping, attributed to the doping induced chemical pressure. In addition, the room temperature switchable magnetodielectric effect is witnessed for the doped BiFeO₃ compounds, due to the quadratic magnetoelectric coupling. This indicates the improved magnetoelectric coupling in BiFeO₃ with the Ca and Ba doping. This is essentially due to the enhanced magnetic ordering and reduced leakage current in BiFeO₃ after the doping.