Majlesi Journal of Telecommunication Devices
Volume:11 Issue: 2, Jun 2022

In this article, a new method is proposed to find tumor's location. This process is based on the arrangement of sensors; the phase and distance to the cancer are given as well. Extraction of tumor distance and phase by Snell's law is the number of received pulses and the delay of receiving Signal. The transmitter antenna is in a fixed position, and the receiver rotates at a certain angular velocity around the tissue. Considering this information, a package solution in polar coordinates is presented. Meanwhile, angle and range information is extracted. Then the maximum probability estimate of the target location is given. This paper applies experimentally to simulated random data.

This paper investigates the effects of the uniaxial tensile strain on the performance of an all silicon junction-less tunneling field-effect transistor (JLTFET) for analog and digital applications. The behavior of the JLTFET under global and local uniaxial strain are studied based on the energy band diagram at ON, OFF, and ambipolar states. Under local uniaxial tensile strain, it has been observed that the tunneling length at the channel/source interface in the ON state has been decreased and at the channel/drain interface in the OFF state has been increased. Simulations illustrate improvements in ON current, ION/IOFF and steep sub threshold swing (SS) and superior transconductance (gm). The strained JLTFET, also demonstrates capability for low-voltage application and high cut-off frequency (fT) and suppressed ambipolar current (Iamb).

In this paper, a hierarchical routing approach based on network clustering and using mobile sinks is proposed in WSN. The first, second, and third levels of hierarchy are composed of sensors, cluster heads (CHs) and mobile sinks (gateways), respectively. The most important challenges in the second level of hierarchy are: 1) election of the most suitable node as CH, and 2) reduction of communication overhead of CH election algorithm. Mobile gateway uses different data transfer technologies (e.g. SMS, WiFi, and 3G) and each communication technology has different characteristics in terms of cost, energy consumption pattern, etc. However, the characteristics of available mobile gateway(s) are ignored in designing CH election algorithm in previous studies. Designing CH election algorithm without considering the characteristics of gateways may lead to problems such as increasing data transfer costs and network fragmentation. Thus, unlike previous studies, a new fitness function is designed with respect to local fitness value of a sensor and fitness value of its available mobile sink(s). In addition, an auction-based method is adopted to control communication overhead of CH election algorithm. The performance of the proposed approach in name DACMS is evaluated in OPNET 14.5 simulation platform. The simulation results show that DACMS outperforms MECA.

The main task of a network-connected SOP is to improve power quality in an active distribution network. In the references, two control modes are created for SOP operation using back-to-back voltage source converters. Using these two modes depends on the distribution network conditions in which the SOP is located. The first is power control, which is provided by independent control of real and reactive power. The second mode is source restoration which with a voltage controller makes it possible to feed isolated loads due to network faults. In this research, an optimal method is presented based on the several SOPs’ performance for active distribution networks and with the help of it, it is presented using self-healing capability based on energy optimization that is presented. Compared to conventional switches, the coordination of multiple SOPs can provide voltage support and effectively increase the source restoration range to improve the load restoration level. Surveys and simulations in the standard IEEE 33-bus network in various scenarios show that with a combination of network reconfiguration and SOPs, loads in the power outage area are fully restored, which effectively improves the flexibility of distribution networks

Machine learning is one of the most practical branches of artificial intelligence that tries to provide algorithms by which the system can analyze a set of data in different formats. Machine learning algorithms are widely used in biomedicine, bioinformatics and neuroscience. The main goal of this paper is to propose the latest applications of machine learning in bioinformatics and neural imaging and to introduce new branches of research. In this article, the application of four indicators of machine learning techniques in the field of bioinformatics is examined. The four categories of techniques studied include clustering, classification, dimensionality, and deep learning. In this paper, we also show that machine learning techniques can be successfully used to address common bioinformatics challenges such as gene expression, DNA methylation identification, mRNA expression, patient classification, brain network analysis, protein chain identification, clustering, and biomarker identification. In each section, some efficient articles with technical details are discussed separately. The results of some papers are also reported in terms of accuracy, database and techniques used.

Recently, cloud computing has emerged as one of the most promising technologies in the healthcare industry, particularly during the coronavirus (COVID-19) pandemic. In this pandemic, the volume of data generated from various sources is increasing which is needs novel technologies for data storage systems, and storage mechanisms. Cloud computing is considered an unsung hero in the healthcare context which provides new services in a simple, cost-efficient model. Furthermore, it can obtain the healthcare data from various sources, mixing, and evaluating the data in real-time, and allows physicians to access patient records at any place and anytime. During the COVID-19 pandemic, the request for online services has been growing which shifts working patterns towards working at home as a protective measure in order to prevent the virus. Since the development of cloud computing in healthcare is happening at fast rates, it has expected that a key part of the healthcare services into transfer onto the cloud to improve outcomes of healthcare service. However, health cloud applications may have security risks, raise the awareness of users about the threats when using unsecured devices may decrease these risks the present paper discusses the concept of cloud computing, its role in the healthcare system by highlighting the COVID-19 pandemic as well as its challenges in the healthcare system.