An intelligent railway surveillance framework based on recognition of object and railway track using deep learning

Multimedia Tools and Applications - In high speed railways, the intelligent railway safety system is necessary to avoid the accidents due to collision between trains and obstacles on the railway...     

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.     

A grey approach for forecasting in a supply chain during intermittentdisruptions

The supply chains today have become vulnerable to frequent disruptions, and with continuing emphasis on efficiency, lacks robustness to deal with them. A part of the solution lies in forecasting the disruption beforehand and the other part in knowing which policies will suit such disrupted conditions best. Accurate and immediate forecasts are a must in a supply chain and hence play a huge role in stabilizing. This study compares the performance of three established forecasting methods (moving average, weighted moving average and exponential smoothing) as well as grey prediction method, during disruptions and stable situations. The experiments are performed in the form of discrete event simulation, on a four stage beer game settings. The results show that moving average and weighted moving average methods become incompetent during disruptions, and are useful only during stable times, when the demand hovers around a predefined mean value. Exponential smoothing and grey method seems to give better results during disruptions and also during stable times in upstream tiers. Grey prediction method in particular is the best method when the disruption frequency is high and also when the disruption impact is gradual rather than sudden.     

Low complexity adaptation for SISO channel shortening equalizers

Since the days of Digital Subscriber Links (DSL), time domain equalizers (TEQ's) have been used to combat time dispersive channels in Multicarrier Systems. In this paper, we propose computationally inexpensive techniques to recompute TEQ weights in the presence of changes in the channel, especially over fast fading channels. The techniques use no extra information except the perturbation to the channel itself, and provide excellent approximations to the new TEQ weights. Adaptation methods for two existing Channel shortening algorithms are proposed and their performance over randomly varying, randomly perturbed channels is studied. The proposed adaptation techniques are shown to perform admirably well for small changes in channels for OFDM systems.     

Novel surface modified polymer–lipid hybrid nanoparticles as intranasal carriers for ropinirole hydrochloride: in vitro, ex vivo and in vivo pharmacodynamic evaluation

Here we report fabrication and evaluation of novel surface modified polymer–lipid hybrid nanoparticles (PLN) as robust carriers for intranasal delivery of ropinirole hydrochloride (ROPI HCl). Sustained release, avoidance of hepatic first pass metabolism, and improved therapeutic efficacy are the major objectives of this experiment. PLN were fabricated by emulsification-solvent diffusion technique and evaluated for physicochemical parameters, in vitro mucoadhesion, in vitro diffusion, ex vivo permeation, mucosal toxicity and stability studies. Box-Behnken experimental design approach has been employed to assess the influence of two independent variables, viz. surfactant (Pluronic F-68) and charge modifier (stearylamine) concentration on particle size, ζ-potential and entrapment efficiency of prepared PLN. Numerical optimization techniques were used for selecting optimized formulation sample, further confirmed by three dimensional response surface plots and regression equations. Results of ANOVA demonstrated the significance of suggested models. DSC and SEM analysis revealed the encapsulation of amorphous form of drug into PLN system, and spherical shape. PLN formulation had shown good retention with no severe signs of damage on integrity of nasal mucosa. Release pattern of drug-loaded sample was best fitted to zero order kinetic model with non-Fickian super case II diffusion mechanism. In vivo pharmacodynamic studies were executed to compare therapeutic efficacy of prepared nasal PLN formulation against marketed oral formulation of same drug. In summary, the PLN could be potentially used as safe and stable carrier for intranasal delivery of ROPI HCl, especially in treatment of Parkinson’s disease.     

Modelling of attenuation of Lamb waves using Rayleigh damping: Numerical and experimental studies

In this study, the Lamb mode attenuation constants were derived in terms of the attenuation coefficient, group velocity and central frequency of excitation of the Lamb mode, using the Rayleigh damping model. Attenuation of Lamb waves, both fundamental symmetric and anti-symmetric modes, propagating through viscoelastic media (cross-ply glass/epoxy laminate) was modelled using the Finite Element Method. Numerically simulated attenuation of Lamb waves using Lamb mode attenuation constants was found to be in good agreement with the assumed attenuation. Experiments were performed on a quasi-isotropic laminate, employing air-coupled ultrasonic transducers, to measure the attenuation coefficient. Lamb mode attenuation constants, computed using the attenuation coefficient, were used to model the attenuation of the Lamb mode in quasi-isotropic laminates. Numerically simulated amplitude variation was found to be in good agreement with that computed from experiments.     

Failure probability evaluation of passive system using fuzzy Monte Carlo simulation

Passive systems have become an inherent feature of the advanced reactors. The main reason being the passive systems are, theoretically, more reliable than the active ones. Nevertheless the passive system may fail to fulfill its mission not only because of a consequence of classical mechanical failure of component (passive or active) of the passive system, but also due to the deviation from expected behavior due to physical phenomena mainly related to thermal hydraulic or due to different boundary or initial conditions. In this paper the methodology used for performing the passive system reliability analysis has been discussed. A case study on passive decay heat removal system (PDHRS) of large sized pressurized heavy water reactor (PHWR) has been discussed. Thermal hydraulic analysis have been carried out by using RELAP5 code to generate the response surface (from various ranges of identified key parameter values), keeping the criterion as clad surface temperature exceeding certain critical value. Some uncertainties, due to incomplete information, cannot be handled satisfactorily in the probability theory and the fuzzy set theory is more appropriate. In this study the random variables are considered as fuzzy numbers and the fuzzy set theory is employed. In addition, the Monte Carlo simulation technique is utilized to evaluate the probability of failure of system.