Smart Edge Computing for 5 g/6 g Satellite IOT for Reducing Inter Transmission Delay

Mobile Networks and Applications - 5G/6G communication are first generation high speed wireless communication network which integrates the aerial data, terrestrial data and maritime data via...     

Cooperative Diversity in Secondary Systems: Efficient Relaying Protocol for Cognitive Radio

Wireless Personal Communications - This paper considers half-duplex cooperative spectrum sharing scheme where both primary and secondary systems mutually cooperate with each other to exploit...     

Electromechanical analytical model of shape memory alloy based tunable cantilevered piezoelectric energy harvester

International Journal of Mechanics and Materials in Design - The resonant frequency of electromechanical energy harvester should be tuned to ambient frequency so as to maximize the harvester power....     

Decay Rate Kinetics of Ozone Gas in Rice Grains

The present study was carried out to evaluate the effects of ozone on rice grains for the following three conditions: saturation time, decay rate, and half-life of ozone. Experiments were performed in different bed thicknesses (5 and 10 cm) and moisture content (11.4 and 14.2% wb) at atmospheric conditions. The lowest saturation time of ozone was 119 min, with the concentration of 516 ppm for rice grains ozonated at 5-cm bed thickness with 11.4% (wb) moisture content. The decay rate kinetics of ozone obtained were consistent with a first-order model. Regarding the half-life of ozone, the lowest value obtained was 6.78 min for rice grains ozonated at 10-cm bed thickness with 14.2% (wb) moisture content.     

Discrete GWO Optimized Data Aggregation for Reducing Transmission Rate in IoT

The conventional hospital environment is transformed into digital transformation that focuses on patient centric remote approach through advanced technologies. Early diagnosis of many diseases will improve the patient life. The cost of health care systems is reduced due to the use of advanced technologies such as Internet of Things (IoT), Wireless Sensor Networks (WSN), Embedded systems, Deep learning approaches and Optimization and aggregation methods. The data generated through these technologies will demand the bandwidth, data rate, latency of the network. In this proposed work, efficient discrete grey wolf optimization (DGWO) based data aggregation scheme using Elliptic curve Elgamal with Message Authentication code (ECEMAC) has been used to aggregate the parameters generated from the wearable sensor devices of the patient. The nodes that are far away from edge node will forward the data to its neighbor cluster head using DGWO. Aggregation scheme will reduce the number of transmissions over the network. The aggregated data are preprocessed at edge node to remove the noise for better diagnosis. Edge node will reduce the overhead of cloud server. The aggregated data are forward to cloud server for central storage and diagnosis. This proposed smart diagnosis will reduce the transmission cost through aggregation scheme which will reduce the energy of the system. Energy cost for proposed system for 300 nodes is 0.34μJ. Various energy cost of existing approaches such as secure privacy preserving data aggregation scheme (SPPDA), concealed data aggregation scheme for multiple application (CDAMA) and secure aggregation scheme (ASAS) are 1.3 μJ, 0.81 μJ and 0.51 μJ respectively. The optimization approaches and encryption method will ensure the data privacy.     

Association Rule Mining Frequent-Pattern-Based Intrusion Detection in Network

In the network security system, intrusion detection plays a significant role. The network security system detects the malicious actions in the network and also conforms the availability, integrity and confidentiality of data information resources. Intrusion identification system can easily detect the false positive alerts. If large number of false positive alerts are created then it makes intrusion detection system as difficult to differentiate the false positive alerts from genuine attacks. Many research works have been done. The issues in the existing algorithms are more memory space and need more time to execute the transactions of records. This paper proposes a novel framework of network security Intrusion Detection System (IDS) using Modified Frequent Pattern (MFP-Tree) via K-means algorithm. The accuracy rate of Modified Frequent Pattern Tree (MFPT)-K means method in finding the various attacks are Normal 94.89%, for DoS based attack 98.34%, for User to Root (U2R) attacks got 96.73%, Remote to Local (R2L) got 95.89% and Probe attack got 92.67% and is optimal when it is compared with other existing algorithms of K-Means and APRIORI.     

Development of porous defects in plasma membranes of adenosine triphosphate-depleted Madin-Darby canine kidney cells and its inhibition by glycine

Studies during the past decade have led to the recognition of a fundamental, widely expressed mechanism of structural damage in energy-deprived cells, which is suppressed by physiologic levels of glycine and is independent of Ca2+ availability or alterations of cytosolic free Ca2+. To gain insight into this process, Madin-Darby canine kidney (MDCK) cells were depleted of adenosine triphosphate (ATP) by a mitochondrial uncoupler in glucose-free medium, and intracellular free Ca2+ was clamped at 100 nM to avoid calcium cytotoxicity. Although the ATP-depleted cells swelled and blebbed and their plasma membranes appeared to be under tension, they nevertheless became permeable to macromolecules. The plasma membranes of these cells retained structural continuity, as determined by morphologic observations, and confocal microscopy of a plasma membrane protein label (Biotin: Ultra Avidin-Texas Red) and a lipid label (NBD-sphingomyelin). Using fluoresceinated dextrans of graded molecular size, membrane permselectivity was examined noninvasively by confocal microscopy. Measured as inside/outside ratios of fluorescence intensity, the permeability indices showed progressively greater restriction to diffusion of increasingly larger dextran molecules across plasma membranes, with sharp break-points between 70,000 and 145,000 daltons (d). The results indicated that the membranes behaved as if they were perforated by water-filled channels or "pores," with size-exclusion limits of molecular dimensions. The membrane defects evolved from small pores permeable only to propidium iodide (668 d) and the smallest dextran (4,000 d), before enlarging with time to become permeable to larger dextrans. Inclusion of glycine during ATP depletion did not affect cell swelling or blebbing but completely prevented the development of permeability defects. Treatment of cells before ATP depletion with a membrane-impermeant homobifunctional "nearest neighbor" cross-linking agent, 3,3' dithiobis(sulfosuccinimidylpropionate), suppressed the development of permeability defects, even in the absence of glycine. These observations suggest that the cellular abnormality that is suppressed by glycine involves rearrangement of plasma membrane proteins to form water-filled pores large enough to leak macromolecules.     

A review of channel estimation and security techniques for CRNS

Cognitive Radio Network (CRN) is an intelligent wireless communication system that adapts itself to variations in the incoming radio frequency stimuli by modifying the operating parameters. Using the spectrum sensing techniques, the idle channels are detected, and allocated to the Secondary Users (SUs). The existing cooperative spectrum sensing techniques such as centralized sensing technique, Distributed sensing technique, and External sensing technique exploit efficient prediction models for allocating the frequency spectrum to SUs. For an optimal assignment of the channel using channel parameters, the channel estimation techniques such as pilot-assisted channel estimation, blind and semi blind estimation technique, and decision directed channel estimation technique are analyzed. The flexible nature of the CRN introduces various security attacks such as Primary User Emulation Attack, Objective Function Attack, Jamming Attack, Spectrum Sensing Data Falsification (SSDF), Control Channel Saturation DoS Attack (CCSD), Selfish Channel Negotiation (SCN), Sinkhole Attacks, HELLO Flood Attacks and Lion Attack. From the surveyed results, it is observed that the existing spectrum sensing, and prediction-based techniques consume more energy, and minimal data transmission rate for detecting the idle channel. Further, the end-to-end delay, energy consumption, end-to-end delay, and bandwidth are not minimized by the existing techniques.     

Electrospun MgO/Nylon 6 Hybrid Nanofibers for Protective Clothing

Nano-Micro Letters - Magnesia (MgO) nanoparticles were produced from magnesite ore (MgCO3) using ball mill. The crystalline size, morphology and specific SSA were characterized by X-ray diffraction...