Fractional-Grasshopper Optimization Algorithm for the Sensor Activation Control in Wireless Sensor Networks

Wireless Personal Communications - The progression in wireless sensor network (WSN) has been increased and gained immense attention in computer vision. In WSN, a large number of sensors are...     

3,5-Difluorobenzonitrile: ab initio calculations,FTIR and Raman spectra

Geometry, vibrational wavenumbers and several thermodynamic parameters were calculated using ab initio quantum chemical methods for the 3,5-difluorobenzonitrile molecule. The results were compared with the experimental values. With the help of three specific scaling procedures, the observed vibrational wavenumbers in FTIR and Raman spectra were analysed and assigned to different normal modes of the molecule. Most of the modes have wavenumbers in the expected range and the error obtained was in general very low. Using PEDs the contributions were determined for the different modes to each wavenumber. From the PED, it is apparent that the frequency corresponding to C[triple bond]N stretching contains 87% contribution from the C[triple bond]N stretching force constant and it mixes with the C-CN stretching mode 13 to the extent of 12%. Other general conclusions were also deduced.     

‘Extreme Mass Spectrometry’: the role of mass spectrometry in the study of the Antarctic Environment

A focus on the studies of the Antarctic environment that have been performed by mass spectrometry is presented herein; our aim is to give evidence of the essential role of this instrumental technique in the framework of the scientific research in Antarctica, with a comprehensive review on the main literature of the last two decades. Due to the wideness of the topic, the present review is limited to the determination of organic pollutants, natural molecules and biomarkers in Antarctica, thus excluding elemental analysis and studies on inorganic species. The work has been divided into five sections, on the basis of the considered environmental compartment: air; ice and snow; seawater, pack ice and lakes; soil and sediments; and organisms and biomarkers. Copyright © 2014 John Wiley & Sons, Ltd.     

Direct TLC resolution of atenolol and propranolol into their enantiomers using three different chiral selectors as impregnating reagents

Direct resolution of racemic atenolol and propranolol into their enantiomers was achieved by normal phase TLC on silica gel plates impregnated with optically pure L-tartaric acid, (R)-mandelic acid and (-)-erythromycin as chiral selectors. Different solvent systems were worked out to resolve the enantiomers. Spots were detected using iodine vapour. The TLC method was validated for linearity, limit of detection and limit of quantification. The influence of pH, temperature and concentration of chiral selector was studied.     

Fusion of artificial intelligence and game theory for resource allocation in non-orthogonal multiple access-assisted device-to-device cooperative communication

Device-to-device (D2D) communication offers a low-cost paradigm where two devices in close proximity can communicate without needing a base station (BS). It significantly improves radio resource allocation, channel gain, communication latency, and energy efficiency and offers cooperative communication to enhance the weak user's network coverage. The cellular mobile users (CMUs) share the spectral resources (e.g., power, channel, and spectrum) with D2D mobile users (DMUs), improving spectral efficiency. However, the reuse of radio resources causes various interferences, such as intercell and intracell interference, that degrade the performance of overall D2D communication. To overcome the aforementioned issues, this paper presents a fusion of AI and coalition game for secure resource allocation in non-orthogonal multiple access (NOMA)-based cooperative D2D communication. Here, NOMA uses the successive interference cancellation (SIC) technique to reduce the severe impact of interference from the D2D systems. Further, we utilized a coalition game theoretic model that efficiently and securely allocates the resources between CMUs and DMUs. However, in the coalition game, all DMUs participate in obtaining resources from CMUs, which increases the computational overhead of the overall system. For that, we employ artificial intelligence (AI) classifiers that bifurcate the DMUs based on their channel quality parameters, such as reference signal received power (RSRP), received signal strength indicator (RSSI), signal-to-noise ratio (SNR), and channel quality indicator (CQI). It only forwards the DMUs that have better channel quality parameters into the coalition game, thus reducing the computational overhead of the overall D2D communication. The performance of the proposed scheme is evaluated using various statistical metrics, for example, precision score, accuracy, recall, F1 score, overall sum rate, and secrecy capacity, where an accuracy of 99.38% is achieved while selecting DMUs for D2D communication.