電気通信システムと管理

The satellite communications market is growing and new generation of satellites will have unprecedented levels of flexibility and scalability: future multibeam High Throughput Satellites (HTS) are expected to be able to operate thousands of beams simultaneously. This poses new challenges when it comes to efficiently managing the increasing amount of resources. Two of these challenges are linked to the beam placement (i.e., defining the pointing direction for each beam) and beam shape (i.e., optimizing the gain distribution among covered users) problems. Optimizing these processes could reduce required RF power and enable the accommodation of new users into the system. In this paper, we present an algorithm to address the joint beam placement and beam shape optimization. It consists of an iterative approach combining a placement heuristic and a gradient descent-based method. The algorithm decides the total number of 
beams needed and provides their pointing directions and shapes. We analyze the performance of this algorithm in a high-dimensional scenario based on realistic operational data, considering elliptical shapes with variable semi axes and relative rotation. We show this method provides higher gain to users and reduces satellite power consumption in comparison to other approaches from literature

The transfer of information from source to destination i.e transmitter to receiver is called the communication. Basically communication is possible in two ways they are wire communication and the other one is wireless communication. The satellite communication is a best example for the wireless communication. The Satellite communication has served making in many ways from instance its is used to predict weather and broadcast storm warnings and also provides a wide range of communication services in the fields of relaying television programs, point to point communication, voice, data, internet, fax. 

Ultra wideband (UWB) technology is one of the most widely technologies used in wireless communication system to support the application that required high data rate and high speed. Since the release by the Federal Communications Commission (FCC) of a bandwidth of 7.5GHz (from 3.1GHz to 10.6GHz) for UWB wireless communications, UWB is rapidly developed to justify the needs   of modern wireless communication applications. The development of UWB technology includes antenna as an essential part of wireless communication systems. However, there are more challenges in designing UWB antenna than a narrow band one. A suitable UWB antenna should be capable of operating over an ultra wide bandwidth as allocated by the FCC. At the same time, satisfactory radiation properties over the entire frequency range are also necessary. Besides that, small size, lightweight, low profile and low cost are also features highly required to be in UWB antenna. The  purpose of this work is to design and fabricate  ultra wideband microstrip patch  antenna for wireless application with optimum  performance  such as  wide  bandwidth,  good  matching  impedance,  small  antenna  size exhibits  and  its  E and H–plane radiation patterns are stable over the UWB frequency range . To achieve that, slotted partial ground plane, steps notches at the bottom of the patch and slots on the patch techniques are applied on a conventional rectangular microstrip patch antenna excited directly using microstrip line technique. Designed UWB antenna simulated using Computer Simulation Technology and fabricated on FR4 substrate. Both simulation and measurement results show that UWB antenna has good performance. Return loss results satisfy UWB technology frequency 
range under -10dB; from 3.23 GHz to 10.89 GHz for simulation, while measured return loss slightly shifted to start form 3.8 GHz to 10.6 GHz. Omin-directional radiation patterns in both E and H plane with sufficient gain at different frequencies in UWB frequency band. Therefore, the antenna design has to evolve to meet the new requirements. By considering the increase of low cost, compactness of electronic systems, and a need of embedding two or more narrowband systems together, microstrip patch antennas are most widely candidates used because of their several advantages such as light weight, low volume, low fabrication cost and capability of dual, triple and more frequency operations. For high data rate transmission system and multifunctional devices, we need wideband directional microstrip antennas with constant gain  over the wide frequency range. Designing a low-profile directional microstrip antenna for these applications is very challenging

“8th Global Meet on Wireless and Satellite Communications” will be held in Munich, Germany during May 17-18, 2021. Major attractions of this event would revolve around keynote presentations, oral presentations and poster presentations. This year we are focusing. The term “” is progressively utilized as an equivalent word for Additive Manufacturing. It transforms digital 3D models into strong solid by structure them up in layers. The innovation was first invented during the 1980s, and since that time has been utilized for rapid prototyping (RP). 

“Wireless and Satellite Communications will be held in Munich, Germanyduring May 21-22, 2021 Major attractions of this event would revolve around keynote presentations, oral presentations and poster presentations. This year we are focusing on the theme “Future of Communication in Today’s World”. The term “Wireless” is progressively utilized as an equivalent word for Additive Communication.The aim of this conference is to learn and share knowledge on Wireless Technologies. This Conference provides a forum for exchange of ideas and authoritative views by leading scientists as well as business leaders and investors in this exciting field. Outstandingkeynotespeakers and well known leading scientists and experts from around the globe will be expected to share their knowledge. We welcome papers describing advanced prototypes, systems, tools and techniques as well as general survey papers indicating future directions are also encouraged. The papers will be reviewed by the Technical Committee on the basis of originality, quality, and relevance to the conference themes. The conference program will include both oral and poster presentations. 

Discussions about the application of artificial intelligence (AI) in healthcare often span multiple areas, most commonly about making more accurate diagnoses, identifying at-risk populations, and better understanding how individual patients will respond to medicines and treatment protocols. To date, there has been relatively little discussion about practical applications of AI to improve medication management across the care continuum, an area this article will address

Osteoarthritis (OA) is the most common reason of disability among the ageing population. The awareness   of machine learning as a tool in medicine is growing rapidly and has provided new avenues for research into a number of diseases and infections. Creating better predictive models for these diseases could provide opportunities for better care, which we have applied to osteoarthritis, a degenerative disease that affects a large number of both gender in older population. A number of studies have been undertaken in order to understand the prediction of Osteoarthritis risks using data mining techniques.  Hence, this study is focused at using two different types of s data mining techniques to predict Osteoarthritis risks in Nigerian patients using the Naïve Bayes’ and the K nearest neighbor algorithms.  The performances of these two classification techniques was evaluated in order to determine the most efficient and effective model. To achieve this, a dataset containing patients who have participated in an osteoarthritis treatment program was used and analyzed.   The Naïve Bayes’ showed a higher accuracy with lower error rates compared to that of the KNN method while the evaluation criteria proved the Naïve Bayes’ to be a more effective and efficient classification techniques for the prediction of Osteoarthritis risks among patients of the study location. Our results shows that it is possible to predict an efficient and effective classifier for Osteoarthritis risks.