Thermodynamic study of the uranium oxycarbide system

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Charged Vector Particles Tunneling From A Pair of Accelerating and Rotating and 5D5D Gauged Super-Gravity Black Holes

The aim of this paper is to study the quantum tunneling process for charged vector particles through the horizons of black holes by using Proca equation. For this purpose, we have consider a pair of charged accelerating and rotating black holes with NUT parameter and a black hole in $5D$ gauged supergravity, respectively. Further, we have studied the tunneling probability and corresponding Hawking temperature for both black holes by using WKB approximation.Comment: 17 Pages. Title modified and minor corrections. Submitted for Publication

Thermodynamic Speed of Sound Data for Liquid and Supercritical Alcohols

Because of their caloric and thermal nature, speed of sound data are vital for the development of fundamental Helmholtz energy equations of state for fluids. The present work reports such data for methanol, 1-propanol, 2-propanol, and 1-butanol along seven isotherms in the temperature range from 220 to 500 K and a pressure of up to 125 MPa. The overall expanded uncertainty varies between 0.07% and 0.11% with a confidence level of 95%. The employed experiment is based on a double path length pulse-echo method with a single piezoelectric quartz crystal of 8 MHz, which is placed between two reflectors at different path lengths. Measured speed of sound data for the four alcohols are fitted with double polynomial equations and compared with literature sources

Electro-Absorption Modulator in Lithium Niobate

LLithium niobate presents a good choice for integrated optics in optical communications and networks applications. Titanium diffused waveguides in lithium niobate are low loss and have a high coupling efficiency with single mode optical fibers at 1.55μm wavelength. Lithium niobate has also been extensively used to fabricate modulators owing to its high electro-optic coefficients. The modulators fabricated in lithium niobate suffer primarily from large device footprint which makes it difficult to integrate variety of devices on a single chip. To help overcome this limitation, two device design configurations for electro-absorption modulation is studied. The first architecture consists of a stack of Indium Tin Oxide (ITO)/SiO2/Au films on the lithium niobate waveguide. The second device configuration also consists of ITO/SiO2/Au stack but includes an additional extended TiO2 film over the waveguide. TiO2 film having a refractive index higher than lithium niobate shifts the optical field towards the surface of the waveguide. This helps to enhance light matter interaction with ITO which serves as the active material. Simulation of the device architecture predicts 5.24dB extinction ratio for the first configuration on a 100μm device length, and 3.75dB extinction ratio for the second architecture with a 20μm modulator length. These are highest reported extinction ratio in lithium niobate based modulators for such a small device footprint

Intelligent intrusion detection in low power IoTs

Security and privacy of data are one of the prime concerns in today’s Internet of Things (IoT). Conventional security techniques like signature-based detection of malware and regular updates of a signature database are not feasible solutions as they cannot secure such systems effectively, having limited resources. Programming languages permitting immediate memory accesses through pointers often result in applications having memory-related errors, which may lead to unpredictable failures and security vulnerabilities. Furthermore, energy efficient IoT devices running on batteries cannot afford the implementation of cryptography algorithms as such techniques have significant impact on the system power consumption. Therefore, in order to operate IoT in a secure manner, the system must be able to detect and prevent any kind of intrusions before the network (i.e., sensor nodes and base station) is destabilised by the attackers. In this article, we have presented an intrusion detection and prevention mechanism by implementing an intelligent security architecture using random neural networks (RNNs). The application’s source code is also instrumented at compile time in order to detect out-of-bound memory accesses. It is based on creating tags, to be coupled with each memory allocation and then placing additional tag checking instructions for each access made to the memory. To validate the feasibility of the proposed security solution, it is implemented for an existing IoT system and its functionality is practically demonstrated by successfully detecting the presence of any suspicious sensor node within the system operating range and anomalous activity in the base station with an accuracy of 97.23%. Overall, the proposed security solution has presented a minimal performance overhead.</jats:p