Telecommunications System & Management

We are pleased to welcome you to the “2nd International Conference on Automation and Artificial Intelligence” after the successful completion of the series of Artificial Intelligence 2020. The congress is scheduled to take place in the beautiful city of London, UK, on June 15-16, 2021. This Artificial Intelligence 2021 conference will provide you with an exemplary research experience and huge ideas. The perspective of the Artificial Intelligence Conference is to set up transplant research to help people understand how treatment techniques have advanced and how the field has developed in recent years. Conferenceseries proffers our immense pleasure and honour in extending you a warm invitation to attend Artificial Intelligence 2021 on June 15-16, 2021 in London, UK. It is focusing on “Innovations and Advancements in Automation and Artificial Intelligence”, to enhance and explore knowledge among Artificial Intelligence community and to establish corporations and exchanging ideas. Providing the right stage to present stimulating Keynote talks, Plenary sessions, Discussion Panels, B2B Meetings, Poster symposia, Video Presentations and Workshop Artificial Intelligence anticipates over 200 participants around the globe with path breaking subjects, discussions and presentations. This will be a splendid feasibility for the researchers, delegates and the students from Global Universities and Institutes to interact with the world class scientists, speakers, Analyst, practitioners and Industry Professionals. Conference Series invites all the experts and researchers from the Automation and Artificial Intelligence sector all over the world to attend “International Conference on Automation and Artificial Intelligence (Artificial Intelligence 2021) which is going to be held on June 15-16, 2021 in London, UK. Artificial Intelligence 2021 conference includes Keynote presentations, Oral talks, Poster Presentations, Workshops, and Exhibitors. Artificial Intelligence is a region of software engineering that emphasises the production of intelligent machines that work and respond like people. Artificial Intelligence is expert in studying how human brain thinks, learn, decide, and work while trying to solve a problem, and then using the products of this study as a source of increasing smart software and systems. In the real life, the knowledge has some undesirable properties. In the modern world, Artificial Intelligence can be used in many ways to control robots, Sensors, actuators etc., An Automation system is a system that controls and displays building organisation. These systems can be established in a few typical ways. In this segment, a general construction frame work for a structure with complex requirements due to the action such as a consulting room will be described. Actual scheme frequently have some of the features and components described here but not all of them. The Automation level consists of all progressive controls that regulate the field level devices in actual time. Online transaction is broadly utilized nowadays. This is one of the best example of Automation. In online shopping the imbursement and checkout are through online conversation system. The most other engineering majors work with Artificial Intelligence, but the heart of Artificial Intelligence is Automation and Automation Engineering across all the disciples. Artificial Intelligence 2021 conference is also comprised of Best Post Awards, Best Oral Presentation Awards, Young Researchers Forums (YRF) and also Video Presentation by experts. We are glad to welcome you all to join and register for the “International Conference on Automation and Artificial Intelligence” which is going to be held during June 15-16, 2021 at London, UK. Our Mission: • To provide the best platform were various ideas can be shared and information can be discussed. • To conduct conferences annually in each and every field of life science in various parts of the world to target maximum audiences. • To conduct outstanding events with our hard work. • To create some value worldwide.

Blockchains  are  a  relative  new  concept  that  started  out  when  Bitcoin  and  the  original Whitepaper  came  out,  in  fact,  Satoshi  Nakamoto’s  Whitepaper  didn’t  even  mention  the  word Blockchain, so how did this even became a thing?

Blockchains are (most of them) ledgers that distribute data usually in a decentralised and public  form,  that  means  that  once  the  information  is  registered,  theoretically  it  cannot  be manipulated  or  altered  which  makes  a  great  use  for  data  management  such  as  logistics,  health records, and of course Money!

Bitcoin is not only the first Blockchain created, it was the first use of this technology and the first  successful  implementation.  Now  governments,  companies,  and  regular  people  from  any country, social class or economic background can access financial services that are not tied up to a government or backed by a commodity.

Bitcoin is not owned by anything or anybody which makes it a perfect tool for economic autonomy and the separation of governments and money. Blockchains will record and storage the world’s data so we can finally move to a digital world.

With the tremendous increase in complexity of integrated circuits having many multifunctional devices on the same board, rapidly shrink the interconnection line width to sub micro meter dimensions levels. The reduced device size can result in the reduced intrinsic switching time, the reduced power consumption as well as the reduced device cost. The devices dramatic miniaturization depends on novel lithographic processes and a high accuracy in mask-wafer alignment technique. Moire signal sensing technology can provide ultrahigh alignment accuracy up to less than +/- 50 nm. To achieve high accuracy in mask-wafer alignment, it required initial alignment to be done with the help of microscopes to bring the mask-wafer alignment grating pitch marks within the moire signal capture range. We have proposed two steps with coarse and fine mask-wafer alignment to make the process automatic without a microscope. When a laser beam is passed through a pair of identical gratings, of say 25 nm pitch, a relative displacement in their position gives a highly periodic signal called “moire” signal. This moire signal is suitably amplified, processed and digitalized to find out the maximum and the minimum values of the moire signal to compute its inverted moire signal Iinv and their difference error signal Idiff using Iinv = A + B – I and Idiff = Iinv – I = (A + B) – 2I, where A, B, and I are maximum, minimum and instantaneous digital values of the moire signal. A novel method was developed to align mask and wafer with placement accuracy estimated to be +/- 40 nm to achieve automatic alignment accuracy to be better than +/- 50 nm. Figure 1 and figure 2 show a setup for feasibility experiments with moire signals and digitalized moire signals with alignment marks, respectively.

The flexibility of bolted assemblies of thin parts is a significant parameter, especially in calculating the load distribution between the various fasteners in an assembly. This characteristic is poorly understood in the case of assemblies that are working both in plastic deformation- shearing and friction. The present study firstly focuses on flexibility of an assembly working only by friction. It highlights the influence of pre-stressing and the coefficient of friction on flexibility as also on hysteresis and assesses the influence of the assembled parts’ geometrical characteristics. The study then goes on to consider a hybrid load transfer assembly. Simulations performed using ABAQUS software provided insight as to how the joint behaves in relation to the pre-stress applied. The results are compared to the case of an assembly working without pre-stress. Using these simulations, a model for determination is proposed. This allows the apparent flexibility of the fastener to be calculated, dissociating the case of apparent flexibility on the first loading cycle needed to calculate the load transfer from the apparent flexibility of the following loading cycles. The formulations proposed thus allow the behaviour of a hybrid load transfer fastener to be characterised in relation to the transferred load FT and a dimensionless parameter characterising the latter’s global behaviour (adhesion or slipping).

 In a femtocell network , which is configured as open access, a user from a neighboring cell preferably from a different type of cell eg.(Macro, Pico or micro cell), can make handover to the femtocell network through handover for better coverage and enhance there channel capabilities for better user experience. To avoid any disruption of service for users, which can happen because of ping-pong HO ( handover) it is mandatory to have a effective cell selection method should be in place. In Traditional approach this cell selection method uses RSSI /RSRP value obtained by measurement report, cell load, channel quality etc. to make decision for cell selection for HO. However problem with traditional based approach is that present measured performance does not necessarily reflect the future performance, thus the need for some kind of smart cell selection that can predict the horizon. Subsequently, we present in this paper a reinforcement learning (RL), i.e Q-learning algorithm, as a generic solution for the cell selection problem in a femtocell network.

Non-orthogonal multiple access (NOMA) has emerged as a promising technique to satiate the fifth-generation (5G) requirements like high spectral efficiency, energy efficiency, increased throughput, and optimized sub-channel utilization over the previously deployed orthogonal multiple access (OMA). In this paper, we employ a low-complexity fractional power allocation algorithm to allocate to each user in the Base Stations transmitting area. In this paper, we aim to explore energy efficiency versus spectral efficiency trade-off with the average signal to noise ratio by employing the superposition method to effectively utilize the sub-channel with Successive Interference Cancellation in the downlink case at the receiver end to achieve the expected simulations results. Furthermore, we have also studied the effect on spectral and energy efficiency with an increased number of users in the cellular area. Finally, we have presented simulation results to corroborate our proposed results where SE increases when we increase transmission power and signal to noise ratio.