Localization of sensor nodes in wireless sensor networks using bat optimization algorithm with enhanced exploration and exploitation characteristics

The Journal of Supercomputing - Wireless sensor networks (WSNs) contain sensor nodes in enormous amount to accumulate the information about the nearby surroundings, and this information is...     

Mitigating the Effect of COVID Lockdown Period on Channel and Bandwidth Utilization in Mobile Communication Network in North Western Rajasthan (India)

Wireless Personal Communications - The COVID-19 lockdown has led all the citizens (mobile subscribers) of India to stay at home and rather work from home. The people have started consuming more...     

Suppression of internal browning and maintenance of antioxidants in beeswax plus salicylic acid coated pear fruit during different storage conditions

Postharvest application of edible waxes blended with antioxidants is an effective strategy to regulate postharvest quality and antioxidant losses in fruits. Effect of beeswax coatings (BW 1.0% and 2.0%) alone or enriched with salicylic acid (SA) on antioxidant properties of pear fruit was studied during 67 days of cold storage and 20 days of supermarket storage conditions respectively. Results showed that under both the storage conditions fruits coated with BW + SA maintained higher total phenolic content (TPC), antioxidant activity and ascorbic acid content (AsA) as compared to the control. Furthermore, combined coatings significantly reduced polyphenol oxidase (PPO) activities and inhibited internal browning (IB) in pears throughout cold and supermarket storage. Overall, the BW 2.0% + SA 2.0 mM exhibited the most competitive effect in terms of preserving the antioxidant properties and preventing internal browning in pears during storage.     

Recent Developments in Spatio-Temporal EEG Source Reconstruction Techniques

EEG is gaining recognition in the field of real-time applications. However, the EEG inverse problem leads to poor spatial resolution in brain source localization. This paper presents an overview of the existing EEG inverse solution methods. Further, a comparative analysis of recent techniques has been presented. This work discusses the challenges associated with the existing source reconstruction algorithms. The main focus is on the recent reports in this field that have combined the EEG denoising in the pre-processing phase along with the inverse localization approaches. Out of various existing techniques, SLORETA offers better localization results but its noise sensitivity is very high. It has been validated in a comparative analysis for simulated dipole sources with no noise. To illustrate the advantage of using pre-processed data with inverse localization, the classification accuracy of conventional methods has been compared. The accuracy has been analyzed for depression signals using the Naïve Bayes, RF, and SVM classifiers. The VMD- SLORETA method shows better accuracy as compared to EMD-SLORETA and SLORETA only. The existing EEG localization methods are efficient but the spatial resolution is still to be improved in the presence of various noise sources in raw EEG. More accurate localization is achieved by implementing denoising in combination with the source localization framework. There is a need to investigate further stages of EEG signal processing along with optimal feature selection. Further, additional studies should be conducted to improve the noise sensitivity of other existing localization systems using pre-processing approaches.

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Hybrid intrusion detection and signature generation using Deep Recurrent Neural Networks

Neural Computing and Applications - Automated signature generation for Intrusion Detection Systems (IDSs) for proactive security of networks is a promising area of research. An IDS monitors a...