Surface-assembled Fe-Oxide colloidal nanoparticles for high performance electrocatalytic water oxidation

Nanoscale electrocatalytic materials having enhanced electroactive sites has been considered trendier and can drive kinetically uphill OER at much lower energy cost with high efficiency. However, very complex synthetic strategies, extensive functionalization processes, and less stability have stimulated quest for economically viable, straightforward and facile preparative methods for designing stable, robust and active nanoscale electrocatalysts engaging geologically abundant materials to ensure their industrial implications. Here we present surface-assembled Fe(OH)_x/FeO_x type colloidal catalytic thin-films, with or without post annealing, derived from Fe-colloidal NPs in simple carbonate system for efficient water oxidation. Comprehensive electrochemical studies including cyclic voltammetry, chronoamperometry, chronopotentiometry, impedance spectroscopy, Tafel slope analysis, mass activity, electrochemically active surface area measurements are conducted to comparatively evaluate the performance of simple (FeO_x/HCO₃^?@FTO and annealed (FeO_x/HCO₃^?@FTO₂₅₀, FeO_x/HCO₃^?@FTO₅₀₀) catalysts for oxygen evolution reaction (OER) under employed conditions. The FeO_x/HCO₃^?@FTO₂₅₀ annealed at 250 °C initiates water oxidation at much lower overpotential of 1.52 V vs. RHE with remarkable stability during long-term electrochemical experimentations. In addition to enhanced OER activity as evidence by better onset potential (<1.55 V vs. RHE), lower Tafel slope value (36 mV dec^1?) and negligible charge transfer resistance, the Fe(OH)_x/HCO₃^?@FTO type catalyst presented excellent electroactive nature during long term controlled potential electrolysis experiments where more and more electroactive sites were getting exposed during continuous hours of electrolysis. The catalysts behave as a potential enduring, inexpensive and competent candidate for catalyzing water oxidation reaction when tested under begin conditions.     

Novel sensing and joint beam and null steering based resource allocation for cross-tier interference mitigation in cognitive femtocell networks

Wireless Networks - Cognitive radios and femtocell networks are gaining much popularity due to the formers ability to carry out unlicensed transmission in licensed bands and the latter’s...     

Diagnosing bot infections using Bayesian inference

Prior research in botnet detection has used the bot lifecycle to build detection systems. These systems, however, use rule-based decision engines which lack automated adaptability and learning, accuracy tunability, the ability to cope with gaps in training data, and the ability to incorporate local security policies. To counter these limitations, we propose to replace the rigid decision engines in contemporary bot detectors with a more formal Bayesian inference engine. Bottleneck, our prototype implementation, builds confidence in bot infections based on the causal bot lifecycle encoded in a Bayesian network. We evaluate Bottleneck by applying it as a post-processing decision engine on lifecycle events generated by two existing bot detectors (BotHunter and BotFlex) on two independently-collected datasets. Our experimental results show that Bottleneck consistently achieves comparable or better accuracy than the existing rule-based detectors when the test data is similar to the training data. For differing training and test data, Bottleneck, due to its automated learning and inference models, easily surpasses the accuracies of rule-based systems. Moreover, Bottleneck’s stochastic nature allows its accuracy to be tuned with respect to organizational needs. Extending Bottleneck’s Bayesian network into an influence diagram allows for local security policies to be defined within our framework. Lastly, we show that Bottleneck can also be extended to incorporate evidence trustscore for false alarm reduction.     

Miniaturized humidity and temperature sensing RFID enabled tags

A compact 27‐bit linearly polarized chipless radio frequency identification tag is presented in this research. The proposed tag is designed with an overall tag dimension of 23 × 23 mm². The tag comprises of metallic (copper) rings‐based structure loaded with slots. These slots correspond to a particular sequence of bits. The circular tag is analysed using 2 different substrates, that is, Rogers RT/duroid/5870 and flexible Rogers RT/duroid/5880. The radar cross‐section response of frequency signatured tag is analysed for humidity and temperature sensor designs. Humidity sensing is achieved by deploying a DuPont Kapton HN heat resistant sheet on the shortest slot of the tag, that is, the sensing slot. Temperature sensing is attained using Rogers RT/duroid/5870 and Stanyl polyamide as a combined substrate. Hence, the miniaturized, robust, and flexible tag can be deployed over irregular surfaces for sensing purposes.     

Multi-objective feature subset selection using mRMR based enhanced ant colony optimization algorithm (mRMR-EACO)

In this research, we propose a novel method to find the relevant feature subset by using ant colony optimisation minimum-redundancy–maximum-relevance. The proposed approach considers the significance of each feature while reducing the dimensionality. The performance of proposed algorithm has been compared with existing biologically inspired feature subset selection algorithms. Eight datasets have been selected from UCI machine learning repository for experimentation. The experimental results indicate that the presented algorithm out performs the other algorithms in terms of the classification accuracy and feature reduction.     

Phase Inversion Technique-Based Polyamide Films and Their Applications: A Comprehensive Review

This is a comprehensive review regarding the particulars of phase inversion technique and its significance in polyamide films. Phase inversion is a versatile technique to form thin films of neat polyamide, composite, and blend system. Phase inversion can be induced by polymer solution immersion in nonsolvent, contact with nonsolvent vapor, thermal treatment, solvent evaporation, and quenching. Choice of solvent/nonsolvent system, polyamide, additive, coagulation bath, and film casting conditions are crucial. Only limitation of phase inversion is the requirement of polyamide solubility in suitable solvent. Promising applications of phase inversion polyamide are in fuel cell, gas separation, tissue engineering, and water filtration.     

Investigation of the distortion factor for Bussgang noise cancellation iterative receivers

Orthogonal frequency‐division multiplexing (OFDM) is considered an efficient modulation approach in the field of wireless systems. However, the significant high peak to average power ratios (PAPR) are one of the prominant shortcomings of the OFDM systems leading to severe signal distortions and acute power inefficiency. Iterative receivers, which use Bussgang algorithm approach along with clipping at the transmitter, have been presented in the literature. This methodology is majorly receiver based in order to compensate the effects of the clipping noise that was added at the transmitter. These receivers are used to analyse the distortions of clipping noise directly subtracting from the signals that are received in order to get the original signal. We demonstrate in this study a detailed and technical investigation of the Bussgang noise cancellation (BNC) receiver along with some significant results. Simulation results are presented to show that the BNC iterative receiver does not estimate the accurate clipping noise, and the performance may be improved if at the receiver end, it is somehow capable to analyze the precise clipping noise for each OFDM signal.     

Finding a Pareto Optimal Solution for a Multi-Objective Problem of Managing Radio Resources in LTE-A Systems: A QoS Aware Algorithm

Wireless Personal Communications - Due to ever increasing users demands, fulfilling the needs of growing users is challenging with constrained resources for Long Term Evolution- Advanced (LTE-A)....