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...     

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.     

Microstructural Investigation on Failure of Internal Drive Shaft

17-4 PH stainless steel is used as internal drive shaft material in liquid engine pumps. One of the drive shafts failed during operation. The shaft pieces were in contact for short duration after failure, which has resulted in abrasion of fractured surfaces. Samples from the location of failure were taken, and investigation of the failure was carried out using optical and scanning electron microscopy. The microstructural analysis of the material and fractographic analysis of the fractured surface show that the failure was caused by excessive torsion.     

A.c. conductivity studies on the silver molybdo-arsenate glassy system

A new quaternary fast-ion conducting silver molybdo-arsenate [Agl-Ag₂O-(MoO₃ + As₂O₅)] (SMA) glassy system has been prepared using the melt-quenching technique for various dopant salt (Agl) concentrations by fixing the formers (MoO₃ + As₂O₅) composition and the modifier (Ag₂O) to formers (M/F) ratio. The prepared compounds were characterized by X-ray diffraction. The impedance measurements were made on different Agl compositions of the SMA glasses as a function of frequency (6.5 Hz–65 kHz) and temperature (303–343 K), using the Solatron frequency-response analyser (model 1250). The bulk conductivity and the appropriate physical model (equivalent circuit) of the SMA glass were obtained from the impedance analysis. The a.c. conductivity was calculated for different Agl compositions of SMA glasses at various temperatures and the obtained a.c. conductivity results were analysed using Jonscher's Universal Law. The conduction mechanism for the highest conducting SMA glassy compound has been explained using the diffusion path model.     

Dynamic provisioning in multi-tenant service clouds

Cloud-based systems promise an on-demand service provisioning system along with a ??pay-as-you-use?? policy. In the case of multi-tenant systems this would mean dynamic creation of a tenant by integrating existing cloud-based services on the fly. Presently, dynamic creation of a tenant is handled by building the required components from scratch. Although multi-tenant systems help providers save cost by allocating multiple tenants to the same instance of an application, they incur huge reconfiguration costs. Cost and time spent on these reconfiguration activities can be reduced by re-constructing tenants from existing tenant configurations supported by service providers. Multi-tenant cloud-based systems also lack the facility of allowing clients to specify their requirements. Giving clients the flexibility to specify requirements helps them avoid spending an excessive amount of time and effort looking through a list of services, many of which might not be relevant to them. Moreover, dynamic provisioning in the cloud requires an integrated solution across the technology stack (software, platform and infrastructure) combining functional, non-functional and resource allocation requirements. Existing research works in the area of web service matching, although numerous, still fall short, since they usually consider each requirement type in isolation and cannot provide an integrated solution. To that end, in this paper we investigate the features needed for dynamic service provisioning on the cloud. We propose a novel User Interface-Tenant Selector-Customizer (UTC) model and approach, which enables cloud-based services to be systematically modeled and provisioned as variants of existing service tenants in the cloud. Our approach considers functional, non-functional and resource allocation requirements, which are explicitly specified by the client via the user interface component of the model. To the best of our knowledge, ours is the first such integrated approach. We illustrate our ideas using a realistic running example, and also present a proof-of-concept prototype built using IBM??s Rational Software Architect modeling tool. We also present experimental results demonstrating the applicability of our matching algorithm. Our results show significant reduction in matching time with the help of an elimination process that reduces the search space needed for performing matching.     

Hydrogen production from used lubricating oils

Used lubricating oils (lube oils) are generated throughout the year and collected in central locations in many communities. Disposing lube oil in an improper manner contaminates environment to a great degree. Used lube oil can be valuable as a re-refined lubricant or as an energy source. Lube oil is a complex mixture of aliphatic and polycyclic hydrocarbons formulated to withstand high service temperatures in internal combustion engines. Both synthetic and mineral oils contain a high concentration of hydrogen (about 13–14 wt%). At the Florida Solar Energy Center, we have developed a process that converts lube oils to hydrogen and other valuable low molecular weight hydrocarbons. The lube oil reformation experiments were carried out using several commercially available dehydrogenation catalysts at a range of reactor temperatures and pressures, residence times and steam to carbon ratios. In this paper, the data obtained to date and the results are presented and discussed.     

Mixing matrix estimation using discriminative clustering for blind source separation

Mixing matrix estimation in instantaneous blind source separation (BSS) can be performed by exploiting the sparsity and disjoint orthogonality of source signals. As a result, approaches for estimating the unknown mixing process typically employ clustering algorithms on the mixtures in a parametric domain, where the signals can be sparsely represented. In this paper, we propose two algorithms to perform discriminative clustering of the mixture signals for estimating the mixing matrix. For the case of overdetermined BSS, we develop an algorithm to perform linear discriminant analysis based on similarity measures and combine it with K-hyperline clustering. Furthermore, we propose to perform discriminative clustering in a high-dimensional feature space obtained by an implicit mapping, using the kernel trick, for the case of underdetermined source separation. Using simulations on synthetic data, we demonstrate the improvements in mixing matrix estimation performance obtained using the proposed algorithms in comparison to other clustering methods. Finally we perform mixing matrix estimation from speech mixtures, by clustering single source points in the time-frequency domain, and show that the proposed algorithms achieve higher signal to interference ratio when compared to other baseline algorithms.     

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.     

Characteristic study of N07718 superalloy surface prepared by cold spray

For better performance in erosive–corrosive, wear and other extreme environmental conditions surface properties of metals and alloys are usually altered by different techniques. Amongst the various surface coating techniques cold spraying is a relatively new and less reported method. Coating formation at energy lower than the melting stage of materials brings novelty to this process. In this study surface of UNS No. - N07718 alloy is altered by cold spraying chromium-carbide (nickel-chromium) layer. The microstructure properties of this cold sprayed surface are observed by various characterization techniques and the results are used to study mechanism of coating layer formation by cold spray process. This newly developed cold sprayed surface is found to be eligible for further testing in wear and erosive-corrosive environmental conditions.