Climate-Resilient UAVs: Enhancing Energy-Efficient B5G Communication in Harsh Environments

This paper explores the crucial role of Unmanned Aerial Vehicles (UAVs) in advancing Beyond Fifth Generation (B5G) communication networks, especially in adverse weather conditions like rain, fog, and snow. The study investigates the synergy between climate-resilient UAVs and energy-efficient B5G communication. Key findings include the impact of weather elements on UAV coverage and communication dynamics. The research demonstrates significant enhancements in energy efficiency, reduced interference, increased data transmission rates, and optimal channel gain under various weather conditions. Overall, this paper emphasizes the potential of climate-resilient UAVs to improve energy-efficient B5G communication and highlights technology's role in mitigating climate change's impact on communication systems, promoting sustainability and resilience

Comprehensive Investigation and Evaluation of an Indoor 3D System Performance Based on Visible Light Communication

The abstract discusses the significance of Visible Light Communication (VLC) as an efficient and cost-effective solution in the era of green technology. VLC not only provides illumination but also high-speed data transmission through existing infrastructure, making it ideal for indoor positioning systems (IPS) with minimal interference with the Radio Frequency (RF) spectrum and enhanced security. While previous research has mainly focused on positioning accuracy, this paper delves into the performance evaluation of a VLC-based indoor system. The study examines key performance parameters, namely Signal-to-Noise Ratio (SNR) and path loss, in a Line of Sight (LOS) scenario. It employs a single LED and ten different photodiode (PD) locations in a 3D room. MATLAB simulations demonstrate the system's effectiveness, achieving a good SNR with low path loss. Additionally, the research highlights the importance of optimizing the PD's position to maximize signal strength while minimizing noise and losses

Using Groundwater Flow Model (MODFLOW) As a Management Tool for Targeted Sub-Basins in Sana’a Basin

The numerical modelling (MODFLOW) has emerged as an effective tool for managing groundwater resources and predicting future responses, especially when dealing with complex aquifers systems and heterogeneous formations. MODFLOW model has been used herein as a management tool for the targeted sub- basins (Wadi Bani Hawat sub-basin , Wadi Dhahr & Al-Ghayl sub-basin , Wadi Hamdan & As Sabrah sub-basin and Wadi Ghayman sub-basin); the most important groundwater resources for domestic and agricultural sectors in Sana’a basin . Groundwater extraction from this basin has already exceeded the safe yield of the aquifer, a sharp drop in the water table, and a dry out of most wells. Currently, more than 13000 wells including governmental, private and unauthorized wells are operating within the basin boundary. A conceptual model was designed according to the actual groundwater dynamic flow system in the 2010 Hydrosult Sana’a Basin Model. Also, the governing partial parabolic differential equation was defined, including the vertical conductivity flow between the aquifers. Total groundwater abstraction values were compiled after filtering the available data, including the 2015 NWRA-SB wells inventory data. These data were documented in a database and stored in soft copy (excel form). In this study, three simulations of groundwater development scenarios were distinguished. The first scenario is applied for evaluation of the present status and till 2025. The second and the third scenarios are focused on the effect of water augmentation i.e. decrease the present rate of groundwater abstraction to 30% and 50% respectively, with considering the highly intervention of IWRM structure of Sana\u27a basin on the on-going activities related to change land use, change crop pattern, value chain, marketing, modern irrigation techniques, water harvesting techniques, etc….. Scenario 3 gives a remarkable improvement of the water resources system in the four sub-basins within a reasonable period (in the year 2025), thus, it will keep the water resources sustainability. It is recommended that irrigation systems should be improved with the usage of harvesting water methods to reduce the losses and increase the groundwater recharge respectively in the targeted four sub-basin

A review of Smart Contract Blockchain Based on Multi-Criteria Analysis: Challenges and Motivations

A smart contract is a digital program of transaction protocol (rules of contract) based on the consensus architecture of blockchain. Smart contracts with Blockchain are modern technologies that have gained enormous attention in scientific and practical applications. A smart contract is the central aspect of a blockchain that facilitates blockchain as a platform outside the cryptocurrency spectrum. The development of blockchain technology, with a focus on smart contracts, has advanced significantly in recent years. However research on the smart contract idea has weaknesses in the implementation sectors based on a decentralized network that shares an identical state. This paper extensively reviews smart contracts based on multi criteria analysis challenges and motivations. Therefore, implementing blockchain in multi-criteria research is required to increase the efficiency of interaction between users via supporting information exchange with high trust. Implementing blockchain in the multi-criteria analysis is necessary to increase the efficiency of interaction between users via supporting information exchange and with high confidence, detecting malfunctioning, helping users with performance issues, reaching a consensus, deploying distributed solutions and allocating plans, tasks and joint missions. The smart contract with decision-making performance, planning and execution improves the implementation based on efficiency, sustainability and management. Furthermore the uncertainty and supply chain performance lead to improved users confidence in offering new solutions in exchange for problems in smart contacts. Evaluation includes code analysis and performance while development performance can be under development.Comment: Revie

Delayed presentation of congenital diaphragmatic hernia: a case report

Congenital diaphragmatic hernia (CDH) is known as a structural defect caused by inadequate fusion of the pleuroperitoneal membrane forming the diaphragm, allowing peritoneal viscera to protrude into the pleural cavity. It affects nearly one out of 2500 live births. We here report the case of a six-month-old boy with left diaphragmatic hernia presenting with poor feeding, breathing difficulty, cough, and recurrent pneumonia in the last 2 months. Chest X-ray and computed tomography scan revealed left sided CDH. The defect was corrected through open surgical repair without complications. At 5-month follow-up a radiograph was performed which revealed full recovery. The primary goal of this report was to alert physicians to suspect this diagnosis in patients with unexpected presentation of diaphragmatic hernia

Flexible Beamforming in B5G for Improving Tethered UAV Coverage over Smart Environments

Unmanned Aerial Vehicles (UAVs) are being used for wireless communications in smart environments. However, the need for mobility, scalability of data transmission over wide areas, and the required coverage area make UAV beamforming essential for better coverage and user experience. To this end, we propose a flexible beamforming approach to improve tethered UAV coverage quality and maximize the number of users experiencing the minimum required rate in any target environment. Our solution demonstrates a significant achievement in flexible beamforming in smart environments, including urban, suburban, dense, and high-rise urban. Furthermore, the beamforming gain is mainly concentrated in the target to improve the coverage area based on various scenarios. Simulation results show that the proposed approach can achieve a significantly received flexible power beam that focuses the transmitted signal towards the receiver and improves received power by reducing signal power spread. In the case of no beamforming, signal power spreads out as distance increases, reducing the signal strength. Furthermore, our proposed solution is suitable for improving UAV coverage and reliability in smart and harsh environments.Comment: 6 pages, 7 figure

An Adaptive Multi-Level Quantization-Based Reinforcement Learning Model for Enhancing UAV Landing on Moving Targets

The autonomous landing of an unmanned aerial vehicle (UAV) on a moving platform is an essential functionality in various UAV-based applications. It can be added to a teleoperation UAV system or part of an autonomous UAV control system. Various robust and predictive control systems based on the traditional control theory are used for operating a UAV. Recently, some attempts were made to land a UAV on a moving target using reinforcement learning (RL). Vision is used as a typical way of sensing and detecting the moving target. Mainly, the related works have deployed a deep-neural network (DNN) for RL, which takes the image as input and provides the optimal navigation action as output. However, the delay of the multi-layer topology of the deep neural network affects the real-time aspect of such control. This paper proposes an adaptive multi-level quantization-based reinforcement learning (AMLQ) model. The AMLQ model quantizes the continuous actions and states to directly incorporate simple Q-learning to resolve the delay issue. This solution makes the training faster and enables simple knowledge representation without needing the DNN. For evaluation, the AMLQ model was compared with state-of-art approaches and was found to be superior in terms of root mean square error (RMSE), which was 8.7052 compared with the proportional-integral-derivative (PID) controller, which achieved an RMSE of 10.0592