A study of neutron and gamma radiation effects on transmission of various types of glasses, optical coatings, cemented optics and fiber

A study of radiation effects on various types of glasses, dielectric optical coatings, cemented optics and fiber was undertaken with a view to select them for extreme radiation environments. Samples were exposed to different radiation doses in the Pakistan Research Reactor-I (PARR-I) for neutron and Cobalt 60 source for gamma irradiation. Transmissions were measured before and after irradiation. The dielectric coatings were subjected to additional tests (adhesion, abrasion and humidity, etc.) as per MIL-M-13508C and MIL-C-675C. All 15 glasses studied showed varying amounts of transmission loss as expected, with negligible degradation for three types. Recovery of transmissions with time/ageing was also studied, with more or less complete recovery with temperature annealing. A faster bleaching of darkened/brown glasses was achieved by using UV lamps or UV laser. The dielectric coatings (HR, AR) and one of the two commercial optical cements showed excellent resistance to neutrons and gamma radiations, and could be good candidates for the fabrication and utilization of optical components in extreme radiation environments. The data allowed several Chinese glasses to be studied for the first time.     

Disinfection of wastewaters: high-energy electron vs gamma irradiation

A study was undertaken to examine the sensitivity of a wastewater population of coliphage, total coliforms and total flora present in raw sewage and secondary effluent after irradiating with similar doses delivered by a high-energy electron beam and y -radiation. The electron beam study was conducted on a large scale at the Virginia Key Wastewater Treatment Plant, Miami, Fla. The facility is equipped with a 1.5 MeV, 50 mA electron accelerator, with a wastewater flow rate of 8 ls⁻¹. Concurrent y-radiation studies were conducted at laboratory scale using a 5000 Ci, ⁶⁰Co y -source. Three logs reduction of all three test organisms were observed at an electron beam dose of 500 krads, while at least four logs reduction were observed at the same dose utilizing the y-source.     

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.     

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.     

Tethered space orientation via adaptive sliding mode

Here, we study the problem of a rotating tethered satellite system (TSS) orientation. The rotation TSS is used for propellantless delivery of the payload from low earth orbits to geostationary orbits or other transfer orbits. Driving the angular positions to correct desired orientation in rendezvous and tossing moments, in fact, is important operation in many real sceneries. We suggest the mathematical model describing the dynamics of TSS and catch mechanism/payload rendezvous with external disturbance terms. Here is shown that using sliding mode control (SMC), we are able to control successfully the position of TSS. The conventional and adaptive versions of SMC are considered. We show that SMC with the gain matrix adaptation based on the equivalent control method can significantly reduce the undesirable chattering effect provoking possible damages of TSS. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive image denoising using cuckoo algorithm

This paper presents a novel denoising approach based on smoothing linear and nonlinear filters combined with an optimization algorithm. The optimization algorithm used was cuckoo search algorithm and is employed to determine the optimal sequence of filters for each kind of noise. Noises that would be eliminated form images using the proposed approach including Gaussian, speckle, and salt and pepper noise. The denoising behaviour of nonlinear filters and wavelet shrinkage threshold methods have also been analysed and compared with the proposed approach. Results show the robustness of the proposed filter when compared with the state-of-the-art methods in terms of peak signal-to-noise ratio and image quality index. Furthermore, a comparative analysis is provided between the said optimization algorithm and the genetic algorithm.     

Alpha Fusion Adversarial Attack Analysis Using Deep Learning

The deep learning model encompasses a powerful learning ability that integrates the feature extraction, and classification method to improve accuracy. Convolutional Neural Networks (CNN) perform well in machine learning and image processing tasks like segmentation, classification, detection, identification, etc. The CNN models are still sensitive to noise and attack. The smallest change in training images as in an adversarial attack can greatly decrease the accuracy of the CNN model. This paper presents an alpha fusion attack analysis and generates defense against adversarial attacks. The proposed work is divided into three phases: firstly, an MLSTM-based CNN classification model is developed for classifying COVID-CT images. Secondly, an alpha fusion attack is generated to fool the classification model. The alpha fusion attack is tested in the last phase on a modified LSTM-based CNN (CNN-MLSTM) model and other pre-trained models. The results of CNN models show that the accuracy of these models dropped greatly after the alpha-fusion attack. The highest F1 score before the attack was achieved is 97.45 And after the attack lowest F1 score recorded is 22%. Results elucidate the performance in terms of accuracy, precision, F1 score and Recall.     

Biosynthesis and characterisation of nano‐silica as potential system for carrying streptomycin at nano‐scale drug delivery

A growing trend within nanomedicine has been the fabrication of self‐delivering supramolecular nanomedicines containing a high and fixed drug content ensuring eco‐friendly conditions. This study reports on green synthesis of silica nanoparticles (Si‐NPs) using Azadirachta indica leaves extract as an effective chelating agent. X‐ray diffraction analysis and Fourier transform‐infra‐red spectroscopic examination were studied. Scanning electron microscopy analysis revealed that the average size of particles formed via plant extract as reducing agent without any surfactant is in the range of 100–170 nm while addition of cetyltrimethyl ammonium bromide were more uniform with 200 nm in size. Streptomycin as model drug was successfully loaded to green synthesised Si‐NPs, sustain release of the drug from this conjugate unit were examined. Prolong release pattern of the adsorbed drug ensure that Si‐NPs have great potential in nano‐drug delivery keeping the environment preferably biocompatible, future cytotoxic studies in this connection is helpful in achieving safe mode for nano‐drug delivery.Inspec keywords: silicon compounds, nanofabrication, nanomedicine, drug delivery systems, nanoparticles, X‐ray diffraction, Fourier transform infrared spectra, scanning electron microscopyOther keywords: nanosilica, streptomycin, nanoscale drug delivery, nanomedicine, silica nanoparticles, Azadirachta indica leaves extract, X‐ray diffraction analysis, Fourier transform‐infrared spectroscopy, scanning electron microscopy, cetyltrimethyl ammonium bromide, SiO₂