Live video streaming service with pay-as-you-use model on Ethereum Blockchain and InterPlanetary file system

Wireless Networks - In centralized video streaming platforms, the platform owner, rather than the content producer, controls most of the content uploaded on the centralized video...     

A Generalized Formula for Estimating Pure Alkenes Viscosity

Abstract

The importance of liquid viscosity in chemical process design makes it one of the most measured transport properties. Nevertheless, in the pure-component database, no experimental data on liquid viscosity for nearly 50% of the compounds are available. Therefore, prediction methods for liquid viscosity of alkenes over a wide range of absolute temperature for each components are necessary. Moreover, experimental data measured at lower temperatures are often extrapolated to higher temperatures with erroneous results. To improve liquid viscosity prediction of experimental data to temperatures and carbon numbers, we propose an empirical rule for estimating the viscosity of alkenes compounds. A predictive method, based physical properties (absolute temperature and carbon numbers) as its inputs, to correlate liquid viscosity by the statistical analysis is proposed. For a group of 19 compounds, the mean average absolute deviation was 4.6% for 118 data points. These values are better than other predictive methods and show that the statistical analysis model is stable and can be used to obtain good predictions for compounds that were not used in the model calibration.     

Modeling the rate of corrosion of carbon steel using activated diethanolamine solutions for CO2 absorption

A mechanistic model is developed to investigate the influence of an activator on the corrosion rate of carbon steel in the absorption processes of carbon dioxide (CO₂). Piperazine (PZ) is used as the activator in diethanolamine (DEA) aqueous solutions. The developed model for corrosion takes into consideration the effect of fluid flow, transfer of charge and diffusion of oxidizing agents and operating parameters like temperature, activator concentration, CO₂ loading and pH. The study consists of two major models: Vapor-liquid Equilibrium (VLE) model and electrochemical corrosion model. The electrolyte-NRTL equilibrium model was used for determination of concentration of chemical species in the bulk solution. The results of speciation were subsequently used for producing polarization curves and predicting the rate of corrosion occurring at the surface of metal. An increase in concentration of activator, increases the rate of corrosion of carbon steel in mixtures of activated DEA.     

Fatigue fracture analysis of rotating disks under torque

Ultimate strength and endurance limits of a rotating circular disk of uniform thickness under torque are analytically determined. Let N be the number of cycles the disk is made to rotate at a certain angular velocity V, and under a given torque T. An analytical expression is found that relates V and T to the number N that can cause the disk to fracture due to fatigue.     

Intrusion detection and prevention system for an IoT environment

Internet of Things (IoT) security is the act of securing IoT devices and networks. IoT devices, including industrial machines, smart energy grids, and building automation, are extremely vulnerable. With the goal of shielding network systems from illegal access in cloud servers and IoT systems, Intrusion Detection Systems (IDSs) and Network-based Intrusion Prevention Systems (NBIPSs) are proposed in this study. An intrusion prevention system is proposed to realize NBIPS to safeguard top to bottom engineering. The proposed NBIPS inspects network activity streams to identify and counteract misuse instances. The NBIPS is usually located specifically behind a firewall, and it provides a reciprocal layer of investigation that adversely chooses unsafe substances. Network-based IPS sensors can be installed either in an inline or a passive model. An inline sensor is installed to monitor the traffic passing through it. The sensors are installed to stop attacks by blocking the traffic using an IoT signature-based protocol.     

A Novel Framework for Human Activity Recognition with Time Labelled Real Time Sensor Data

Human activity recognition is an effective approach for identifying the characteristics of historical data. In the past decades, different shallow classifiers and handcrafted features were used to identify the activities from the sensor data. These approaches are configured for offline processing and are not suitable for sequential data. This article proposes an adaptive framework for human activity recognition using a deep learning mechanism. This deep learning approach forms the deep belief network (DBN), which contains a visible layer and hidden layers. The processing of raw sensor data is performed by these layers and the activity is identified at the top most layers. The DBN is tested using the real time environment with the help of mobile devices that contain an accelerometer, a magnetometer, and a gyroscope. The results are analyzed with the metrics of precision, recall, and the F1-score. The results proved that the proposed method has a higher F1_score when compared to the existing approach.     

Optimizing the Roadside Unit Deployment Mechanism in VANET with Efficient Protocol to Prevent Data Loss

Wireless Personal Communications - RTS/ CTS protocol serves multihop wireless networks poorly due to its single-hop design. TDMA protocol surpasses RTS/ CTS but unable to solve the dynamic needs of...     

A novel method for vehicle detection in high-resolution aerial remote sensing images using YOLT approach

Multimedia Tools and Applications - Owing to the innovative challenge stood by an intergovernmental military alliance, we have proposed a model to find novel solutions in the areas of data...     

Simulation and test of a point focused electron beam emitter

We present the design analysis of a point focused electron beam emitter using numerical techniques. Simulation and modeling were performed followed by the calculation of emission parameters using programming codes EGUN and CST-PS. Beam emittance, average current density and perveance were calculated and are in agreement with the experimental values obtained at 10 kV acceleration potential. The emission parameters were evaluated up to 110 kV. This confirms possibilities of potential application of emitter for a linear accelerator.