Random Bichromatic Matchings

Given a graph with edges colored Red and Blue, we study the problem of sampling and approximately counting the number of matchings with exactly k Red edges. We solve the problem of estimating the number of perfect matchings with exactly k Red edges for dense graphs. We study a Markov chain on the space of all matchings of a graph that favors matchings with k Red edges. We show that it is rapidly mixing using non-traditional canonical paths that can backtrack. We show that this chain can be used to sample matchings in the 2-dimensional toroidal lattice of any fixed size ℓ with k Red edges, where the horizontal edges are Red and the vertical edges are Blue. An extended abstract appeared in J.R. Correa, A. Hevia and M.A. Kiwi (eds.) Proceedings of the 7th Latin American Theoretical Informatics Symposium, LNCS 3887, pp. 190–201, Springer, 2006. N. Bhatnagar’s and D. Randall’s research was supported in part by NSF grants CCR-0515105 and DMS-0505505. V.V. Vazirani’s research was supported in part by NSF grants 0311541, 0220343 and CCR-0515186. N. Bhatnagar’s and E. Vigoda’s research was supported in part by NSF grant CCR-0455666.     

Novel Lyapunov-based rapid and ripple-free MPPT using a robust model reference adaptive controller for solar PV system

The technological, economic, and environmental benefits of photovoltaic (PV) systems have led to their widespread adoption in recent years as a source of electricity generation. However, precisely identifying a PV system''s maximum power point (MPP) under normal and shaded weather conditions is crucial to conserving the maximum generated power. One of the biggest concerns with a PV system is the existence of partial shading, which produces multiple peaks in the P–V characteristic curve. In these circumstances, classical maximum power point tracking (MPPT) approaches are prone to getting stuck on local peaks and failing to follow the global maximum power point (GMPP). To overcome such obstacles, a new Lyapunov-based Robust Model Reference Adaptive Controller (LRMRAC) is designed and implemented to reach GMPP rapidly and ripple-free. The proposed controller also achieves MPP accurately under slow, abrupt and rapid changes in radiation, temperature and load profile. Simulation and OPAL-RT real-time simulators in various scenarios are performed to verify the superiority of the proposed approach over the other state-of-the-art methods, i.e., ANFIS, INC, VSPO, and P&O. MPP and GMPP are accomplished in less than 3.8 ms and 10 ms, respectively. Based on the results presented, the LRMRAC controller appears to be a promising technique for MPPT in a PV system.     

A matching game framework for users clustering and resource allocation with wireless power transfer in a CR-NOMA network

This paper investigates the resource allocation in a massively deployed user cognitive radio enabled non-orthogonal multiple access (CR-NOMA) network considering the downlink scenario. The system performance deteriorates with the number of users who are experiencing similar channel characteristics from the base station (BS) in NOMA. To address this challenge, we propose a framework for maximizing the system throughput that is based on one-to-one matching game theory integrated with the machine learning technique. The proposed approach is decomposed to solve users clustering and power allocation subproblems. The selection of optimal cluster heads (CHs) and their associated cluster members is based on Gale-Shapley matching game theoretical model with the application of Hungarian method. The CHs can harvest energy from the BS and transfer their surplus power to the primary user (PU) through wireless power transfer. In return, they are allowed to access the licensed band for secondary transmission. The power allocation to the users intended for power conservation at CHs is formulated as a probabilistic constraint, which is then solved by employing the support vector machine (SVM) algorithm. The simulation results demonstrate the efficacy of our proposed schemes that enable the CHs to transfer the residual power while ensuring maximum system throughput. The effects of different parameters on the performance are also studied.     

An Authentication Based Approach for Prevention of Spectrum Sensing Data Falsification Attacks in Cognitive Radio Network

Wireless Personal Communications - This is the era of Intelligent Cognitive Radio Network (CRN) technology that provides the available spectrum with efficient utilization. Cognitive Radio (CR)...     

Deciding the Word Problem for Ground and Strongly Shallow Identities w.r.t. Extensional Symbols

Journal of Automated Reasoning - The word problem for a finite set of ground identities is known to be decidable in polynomial time using congruence closure, and this is also the case if some of...     

CanarDeep: a hybrid deep neural model with mixed fusion for rumour detection in social data streams

Neural Computing and Applications - The unrelenting trend of doctored narratives, content spamming, fake news and rumour dissemination on social media can lead to grave consequences that range from...     

Biocompatible antimicrobial cotton fibres for healthcare industries: a biogenic approach for synthesis of bio‐organic‐coated silver nanoparticles

Cotton fibres coated with biogenically fabricated silver nanoparticles (SNPs) are most sought material because of their enhanced activity and biocompatibility. After successful synthesis of SNPs on cotton fibres using leaf extract of Vitex negundo Linn, the fibres were studied using diffuse reflectance spectroscopy, scanning electron microscopy, nanoparticle tracking analysis, energy dispersive X‐ray, and inductively coupled plasma atomic emission spectrometry. The characterisation revealed uniformly distributed spherical agglomerates of SNPs having individual particle size around 50 nm with the deposition load of 423 μg of silver per gram of cotton. Antimicrobial assay of cotton–SNPs fibres showed effective performance against pathogenic bacteria and fungi. The method is biogenic, environmentally benign, rapid, and cost‐effective, producing highly biocompatible antimicrobial coating required for the healthcare industry.Inspec keywords: cotton, health care, nanoparticles, coatings, silver, fibres, nanofabrication, scanning electron microscopy, X‐ray chemical analysis, atomic emission spectroscopy, plasma applications, microorganisms, biotechnologyOther keywords: biocompatible antimicrobial cotton fibre coating, healthcare industry, bioorganic‐coated silver nanoparticle synthesis, biogenically fabricated silver nanoparticle, SNP, leaf extraction, Vitex negundo Linn, diffuse reflectance spectroscopy, scanning electron microscopy, nanoparticle tracking analysis, energy dispersive X‐ray spectrometry, inductively coupled plasma atomic emission spectrometry, uniformly distributed spherical agglomerate, antimicrobial assay, pathogenic bacteria, fungi, Ag     

Development and gamma-scintigraphy study of Hibiscus rosasinensis polysaccharide-based microspheres for nasal drug delivery

Objective: This work describes the application of natural plant polysaccharide as pharmaceutical mucoadhesive excipients in delivery systems to reduce the clearance rate through nasal cavity.

Methods: Novel natural polysaccharide (Hibiscus rosasinensis)-based mucoadhesive microspheres were prepared by using emulsion crosslinking method for the delivery of rizatriptan benzoate (RB) through nasal route. Mucoadhesive microspheres were characterized for different parameters and nasal clearance of technetium-99m (^99mTc)-radiolabeled microspheres was determined by using gamma-scintigraphy.

Results: Their Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) studies showed that the drug was stable during preparation of microspheres. Aerodynamic diameter of microspheres was in the range 13.23?±?1.83–33.57?±?3.69?µm. Change in drug and polysaccharide ratio influenced the mucoadhesion, encapsulation efficiency and in-vitro release property. Scintigraphs taken at regular interval indicate that control solution was cleared rapidly from nasal cavity, whereas microspheres showed slower clearance (p?Conclusion: Natural polysaccharide-based microspheres achieved extended residence by minimizing effect of mucociliary clearance with opportunity of sustained delivery for longer duration.     

Domain-specific initial population strategy for compliant mechanisms using customized genetic algorithm

Genetic algorithms (GAs) can precisely handle the discrete structural topology optimization of single-piece elastic structures called compliant mechanisms. The initial population of these elastic structures is mostly generated by assigning the material at random. This causes disconnected or unfeasible designs and further rule-based repairing can result in representation degeneracy. However, the problem-specific initial population can affect the performance of GAs like other operators. In this paper, a domain-specific initial population strategy is developed that generates geometrically feasible structures for path generating compliant mechanisms (PGCMs). It is coupled with the elitist non-dominated sorting genetic algorithm (NSGA-II) which has been customized for structural topology optimization. The performance of initial population strategy over random initialization using customized NSGA-II is checked on single and bi-objective optimization problems. Based on the results, it is observed that the custom initialization outperforms the random initialization by dominating all the solutions and exploring larger area of posed objectives. The elastic structures obtained by solving two examples of PGCMs using domain specific initial population strategy are also presented.