The future Internet of Things (IoT) era is anticipated to support computation-intensive and time-critical applications using edge computing for mobile (MEC), which is regarded as promising technique. However, the transmitting uplink performance will be highly impacted by the hostile wireless channel, the low bandwidth, and the low transmission power of IoT devices. Using edge computing for mobile (MEC) to offload tasks becomes a crucial technology to reduce service latency for computation-intensive applications and reduce the computational workloads of mobile devices. Under the restrictions of computation latency and cloud computing capacity, our goal is to reduce the overall energy consumption of all users, including transmission energy and local computation energy. In this article, the Deep Q Network Algorithm (DQNA) to deal with the data rates with respect to the user base in different time slots of 5G NOMA network. The DQNA is optimized by considering more number of cell structures like 2, 4, 6 and 8. Therefore, the DQNA provides the optimal distribution of power among all 3 users in the 5G network, which gives the increased data rates. The existing various power distribution algorithms like frequent pattern (FP), weighted least squares mean error weighted least squares mean error (WLSME), and Random Power and Maximal Power allocation are used to justify the proposed DQNA technique. The proposed technique which gives 81.6% more the data rates when increased the cell structure to 8. Thus 25% more in comparison to other algorithms like FP, WLSME Random Power and Maximal Power allocation.

Non-Orthogonal Multiple Access (NOMA) in the fifth generation (5G) system is one of the optimistic technologies for wireless radio access networks. Compared to orthogonal multiple accesses (OMA) reduce the spectral efficiency; NOMA provides the best solution by increasing the data rates. This study evaluates NOMA with a downlink in the automatic deployment of multiusers. The outage performance and ergotic sum-rate gain give the NOMA better performance can be concluded at the final results. NOMA provides the Quality of Service (QoS) to the multi-users by considering the power allocation and data rate factors. Here is considered the outage probability will be 1 when it identifies the different user and allocates the data rate and power.

With the advent of massive MIMO and mmWave, Antenna selection is the new frontier in hybrid beamforming employed in 5G base stations. Tele-operators are reworking on the components while upgrading to 5G where the antenna is a last-mile device. The burden on the physical layer not only demands smart and adaptive antennas but also an intelligent antenna selection mechanism to reduce power consumption and improve system capacity while degrading the hardware cost and complexity. This work focuses on reducing the power consumption and finding the optimal number of RF chains for a given millimeter wave massive MIMO system. At first, we investigate the power scaling method for both perfect Channel State Information (CSI) and imperfect CSI where the power is reduced by ��/���� and ��/√���� respectively. We further propose to reduce the power consumption by emphasizing on the subdued resolution of Analog-to-Digital Converters (ADCs) with quantization awareness. The proposed algorithm selects the optimal number of antenna elements based on the resolution of ADCs without compromising on the quality of reception. The performance of the proposed algorithm shows significant improvement when compared with conventional and random antenna selection methods.

Early blight disease caused by Alternaria sp. is one of the most devastating diseases of

Solanaceous crops widely distributed in Sudan. The aim of this study was to determine the

genetic variation among different Alternaria isolates recovered from different Solanaceae

crops showing typical symptoms of early blight disease. Infected leaves of tomato, potato,

eggplant and pepper were collected from different geographical zones in Sudan. The recovered

fungal isolates were identified to the genus level based on cultural and morphological

characteristics. Five representative isolates were sent to the CABI Bioscience, U.K. for confirmation.

The genetic relationship among the isolates was determined using the amplified

fragments length polymorphism (AFLP) technique and the generated data were used to

create similarity matrices using the PAST 3.01 software package. Dendrograms were constructed

based on Jaccard’s similarity coefficients. A total of 70 fungal isolates was recovered

from the tested plants and all of them showed morphological characteristics typical

of Alternaria spp. The conidia appeared in multiple-branched chains with spore sizes in

the range of 2.38−13.09 μm × 12.30−43.63 μm. Therefore, the isolates were identified as

Alternaria alternata (Fr.) Keissl. The identification was then confirmed by CABI.AFLPbased

dendrogram which revealed five clusters with a significant cophenetic correlation

coefficient (r = 0.834) between the dendrogram and the original similarity matrix irrespective

of their geographical origins. Eighteen (75%) of the Alternaria isolated from tomato

leaves were clustered together in cluster I and five isolates formed two separate clusters,

viz. cluster IV (T-Kh5 and T-H1) and cluster V (T-H4 and T-Med2). The remaining isolate,

T-Am5, grouped with one of the potato isolates in cluster III. The other isolates which were

recovered from potato, pepper and eggplants were all separated from the tomato isolates

in the largest cluster.

The column is one of the most significant structural elements, which is designed to support mainly the compressive load. Strengthening of existing reinforced concrete columns is required to enhance ductility and increase load capacity to sustain the overload as sometimes there may be a change in use. Ten rectangular concrete columns were constructed and tested. H/b ratio was kept constant and equals 6 for all columns The aim of this work is to study the behaviour and efficiency of RC columns strengthened with steel jackets subjected to axial load. An experimental study of the behaviour of ten strengthened concrete columns with slenderness ratio (t / b) equals 6 was carried out. Variables such as aspect ratio ( H / b), the volume of steel batten plates, and spacing of steel batten plates at centres ( S) were considered. The results showed that using this method of strengthening is very effective and an increase in the axial load capacity of the strengthened columns is obtained.