A metaheuristic analysis of heat transfer rates through porous fins of tapered and step profiles: a comparative study

Neural Computing and Applications - The advanced high-end gadgets and sophisticated machines require effective mechanism of transferring heat away from the sources. In a large number of...     

Hierarchical Fuzzy Systems Integrated with Particle Swarm Optimization for Daily Reference Evapotranspiration Prediction: a Novel Approach

Water Resources Management - Reference evapotranspiration (ET0) is a crucial element for deriving irrigation scheduling of major crops. Thus, precise projection of ET0 is essential for better...     

In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

Journal of Intelligent Manufacturing - In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size,...     

Biosynthesis of zinc oxide nanoparticles by petals extract of Rosa indica L., its formulation as nail paint and evaluation of antifungal activity against fungi causing onychomycosis

Aim: The authors report the biological synthesis of zinc oxide nanoparticles (ZnO‐NPs) from the petals extract of Rosa indica L. (rose). Its efficacy was evaluated against two dermatophytes: namely: Trichophyton mentagrophytes and Microsporum canis which cause onychomycosis. The activity of antibiotics against the tested dermatophytes was enhanced, when evaluated in combination with ZnO‐NPs. Methods and results: The synthesised ZnO‐NPs were preliminary detected by using ultraviolet UV visible spectroscopy, which showed specific absorbance. The ZnO‐NPs were further characterised by nanoparticle tracking analysis (NTA), Fourier transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), X‐ray diffraction and Zetasizer. Moreover, nanoparticles containing nail paint (nanopaint) was formulated and its antifungal activity was also assessed against T. mentagrophytes and M. canis. ZnO‐NPs and formulated nanopaint containing ZnO‐NPs, both showed significant antifungal activity. The maximum activity was noted against M. canis and lesser against T. mentagrophytes. Minimum inhibitory concentration of ZnO‐NPs was also determined against the dermatophytes causing onychomycosis infection. Conclusion: ZnO‐NPs can be utilised as a potential antifungal agent for the treatment of onychomycosis after more experimental trials.Inspec keywords: diseases, zinc compounds, nanoparticles, nanofabrication, antibacterial activity, microorganisms, nanomedicine, ultraviolet spectra, visible spectra, Fourier transform infrared spectra, transmission electron microscopy, X‐ray diffraction, biomedical materials, patient treatmentOther keywords: zinc oxide nanoparticle biosynthesis, Rosa indica L petals extract, nail paint, antifungal activity evaluation, dermatophyte, Trichophyton mentagrophytes, Microsporum canis, antibiotics activity, ultraviolet‐visible spectroscopy, nanoparticle tracking analysis, Fourier transform infrared spectroscopy, transmission electron microscopy, X‐ray diffraction, zetasizer, antifungal agent, onychomycosis treatment     

Search Strategies for Multiple UAV Search and Destroy Missions

Multiple UAVs are deployed to carry out a search and destroy mission in a bounded region. The UAVs have limited sensor range and can carry limited resources which reduce with use. The UAVs perform a search task to detect targets. When a target is detected which requires different type and quantities of resources to completely destroy, then a team of UAVs called as a coalition is formed to attack the target. The coalition members have to modify their route to attack the target, in the process, the search task is affected, as search and destroy tasks are coupled. The performance of the mission is a function of the search and the task allocation strategies. Therefore, for a given task allocation strategy, we need to devise search strategies that are efficient. In this paper, we propose three different search strategies namely; random search strategy, lanes based search strategy and grid based search strategy and analyze their performance through Monte-Carlo simulations. The results show that the grid based search strategy performs the best but with high information overhead.     

Multiple UAV Coalitions for a Search and Prosecute Mission

Unmanned aerial vehicles (UAVs) have the potential to carry resources in support of search and prosecute operations. Often to completely prosecute a target, UAVs may have to simultaneously attack the target with various resources with different capacities. However, the UAVs are capable of carrying only limited resources in small quantities, hence, a group of UAVs (coalition) needs to be assigned that satisfies the target resource requirement. The assigned coalition must be such that it minimizes the target prosecution delay and the size of the coalition. The problem of forming coalitions is computationally intensive due to the combinatorial nature of the problem, but for real-time applications computationally cheap solutions are required. In this paper, we propose decentralized sub-optimal (polynomial time) and decentralized optimal coalition formation algorithms that generate coalitions for a single target with low computational complexity. We compare the performance of the proposed algorithms to that of a global optimal solution for which we need to solve a centralized combinatorial optimization problem. This problem is computationally intensive because the solution has to (a) provide a coalition for each target, (b) design a sequence in which targets need to be prosecuted, and (c) take into account reduction of UAV resources with usage. To solve this problem we use the Particle Swarm Optimization (PSO) technique. Through simulations, we study the performance of the proposed algorithms in terms of mission performance, complexity of the algorithms and the time taken to form the coalition. The simulation results show that the solution provided by the proposed algorithms is close to the global optimal solution and requires far less computational resources.     

Dynamics and control of vapor recompression distillation

Vapor recompression distillation is an energy integrated distillation configuration which works on the principle of a heat pump. The tight material and energy integration in such columns shows a potential for intricate dynamics. In this paper, a systematic modeling framework is developed which explicitly captures the discrepancies between different material and energy flows present in such columns. This feature is documented to lead to stiff dynamic equations and multiple time-scale dynamics. Through a nested application of singular perturbations, reduced order non-stiff models are derived which capture the dynamics in each time-scale. A hierarchical control strategy is then proposed exploiting this time-scale multiplicity. A case of propane–propylene separation is considered to illustrate these results and demonstrate the effectiveness of the proposed control strategy via a simulation case study.     

Retailers' tagging practices: a potential liability?

This study investigates the coverage of federally mandated information on over‐the‐counter (OTC) drug labels by electronic article surveillance (EAS) tags applied to the exterior of cartons. Using adult‐strength analgesics containing acetaminophen as a case study, researchers investigated the issue in Houston, Texas (24 stores) and Lansing, Michigan (33 stores). The information obscured by EAS tags was identified and classified for a total of 849 packages using a standardized data collection instrument. The results indicated that 293 packages examined, or 34.5%, had information mandated by the US Food and Drug Administration (US FDA) fully or partially obscured by the EAS tags. Retailers and manufacturers should be aware of such practices to reduce potential liability. Recommendations for improving EAS tag usage on OTC products are presented. Copyright © 2004 John Wiley & Sons, Ltd.     

Forecasting the trend of international scientific collaboration

The study demonstrates an integrated method of forecasting the trend of a country’s publications. In this context the paper examines international collaboration in a country’s overall publication and forecasts its future trend. The integrated method is based on regression and scaling relationship. India is taken as a case study for this examination. The study shows some interesting features of India’s publication pattern based on time-series data. One observes exponential nature of her publication growth from 2002 onwards. International collaboration also exhibits exponential growth roughly from the same period. Also one observes the faster growth of international collaborative papers than the overall growth of research papers. The study predicts values of number of internationally collaborative papers for the years 2015 and 2020. The robustness of the method is also demonstrated.     

Students’ affective content analysis in smart classroom environment using deep learning techniques

Multimedia Tools and Applications - In the era of the smart classroom environment, students’ affective content analysis plays a vital role as it helps to foster the affective states that are...