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er for distributed training. The simulation results show that the proposed distributed MARL converges stably in various environments, and performs better than distributed deep reinforcement algorithm.Improvements in transmission and reception sensitivities of radiofrequency (RF) coils used in ultra-high field (UHF) magnetic resonance imaging (MRI) are needed to reduce specific absorption rates (SAR) and RF power deposition, albeit without applying high-power RF. Here, we propose a method to simultaneously improve transmission efficiency and reception sensitivity of a band-pass birdcage RF coil (BP-BC RF coil) by combining a multi-channel wireless RF element (MCWE) with a high permittivity material (HPM) in a 7.0 T MRI. Electromagnetic field (EM-field) simulations, performed using two types of phantoms, viz., a cylindrical phantom filled with oil and a human head model, were used to compare the effects of MCWE and HPM on BP-BC RF coils. EM-fields were calculated using the finite difference time-domain (FDTD) method and analyzed using Matlab software. Next, to improve RF transmission efficiency, we compared two HPM structures, namely, a hollow cylinder shape HPM (hcHPM) and segmented cylinder shape HPM (scHPM). The scHPM and MCWE model comprised 16 elements (16-rad BP-BC RF coil) and this coil configuration demonstrated superior RF transmission efficiency and reception sensitivity along with an acceptable SAR. We expect wider clinical application of this combination in 7.0 T MRIs, which were recently approved by the United States Food and Drug Administration.An increase in the number of transmit antennas (M) poses an equivalent rise in the number of Radio Frequency (RF) chains associated with each antenna element, particularly in digital beamforming. The chain exhibits a substantial amount of power consumption accordingly. Hence, to alleviate such problems, one of the potential solutions is to reduce the number of RFs or to minimize their power consumption. In this paper, low-resolution Digital to Analogue Conversion (DAC) and transmit antenna selection at the downlink are evaluated to favour reducing the total power consumption and achieving energy efficiency in mMIMO with reasonable complexity. Antenna selection and low-resolution DAC techniques are proposed to leverage massive MIMO systems in free space and Close In (CI) path-loss models. The simulation results show that the power consumption decreases with antenna selection and low-resolution DAC. Then, the system achieves more energy efficiency than without low-resolution of DAC and full array utilization.This paper studies the performance of the energy-based sensing procedure in the presence of multipath fading and shadowing effects in terms of its average probability of detection (APD), average receiver operating characteristic (AROC) and the area under the AROC curve (AUC). A new generalization for the class of the fading channel moment generating functions (MGFs) (i.e., factorized power type (FPT) MGF) was proposed and applied for the construction of the unified framework for the analytical treatment of the formulated problem. The contiguity of the proposed model with the existing classical ones (Rayleigh, Nakagami-m, Hoyt, η-μ, κ-μ shadowed and Mixture-Gamma) was demonstrated. Within the assumed MGF representation, the novel closed-form solutions and computationally efficient approximation for APD and AUC are derived. The obtained general expressions were then applied for derivation of the new results for the recent generalized fading channel models Fluctuating Beckmann and Beaulieu-Xie shadowed. For each of the models, high-SNR asymptotic expressions were obtained. Lastly, numeric simulation was performed to verify the correctness of the derived results, to establish the dependencies of the sensing performance quality from the channel parameters and to identify the specific ranges of their asymptotic behavior.The bidirectional reflection distribution function (BRDF) is among the most effective means to study the phenomenon of light-object interaction. It can precisely describe the characteristics of spatial reflection of the target surface, and has been applied to aerial remote sensing, imaging technology, materials analysis, and computer rendering technology. This study provides a comprehensive review of the development of devices to measure the BRDF. We gathered research in the area by using the Web of Science Core Collection, and show that work on the BDRF has been ongoing in the last 30 years. We also describe some typical measurement devices for the BRDF proposed in the literature. Finally, we summarise outstanding problems related to BRDF measurement and propose directions of future research in the area.Wireless Sensor Networks (WSNs) can be defined as a cluster of sensors with a restricted power supply deployed in a specific area to gather environmental data. One of the most challenging areas of research is to design energy-efficient data gathering algorithms in large-scale WSNs, as each sensor node, in general, has limited energy resources. Literature review shows that with regards to energy saving, clustering-based techniques for data gathering are quite effective. Moreover, cluster head (CH) optimization is a non-deterministic polynomial (NP) hard problem. Both the lifespan of the network and its energy efficiency are improved by choosing the optimal path in routing. The technique put forth in this paper is based on multi swarm optimization (MSO) (i.e., multi-PSO) together with Tabu search (TS) techniques. Efficient CHs are chosen by the proposed system, which increases the optimization of routing and life of the network. The obtained results show that the MSO-Tabu approach has a 14%, 5%, 11%, and 4% higher number of clusters and a 20%, 6%, 14%, and 6% lesser average packet loss rate as compared to a genetic algorithm (GA), differential evolution (DE), Tabu, and MSO based clustering, respectively. Moreover, the MSO-Tabu approach has 136%, 36%, 136%, and 38% higher lifetime computation, and 22%, 16%, 51%, and 12% higher average dissipated energy. Thus, the study’s outcome shows that the proposed MSO-Tabu is efficient, as it enhances the number of clusters formed, average energy dissipated, lifetime computation, and there is a decrease in mean packet loss and end-to-end delay.Pressure injuries are wounds caused by reduced blood circulation for regular and repetitive periods when pressing the human body against a hard surface. It is a pathology that needs daily preventive care and health promotion to avoid incidences. Thus, this article aims to validate a platform based on the gamified collaborative practices model to prevent pressure injuries. The methodological contribution is Design Science, and the software was evaluated by 16 wheelchair users who aimed at usability (SUS), user experience (UEQ), and ability to promote the system (NPS). In addition to creating a collaborative network using the interactions that occurred during the platform’s use. Wheelchair users rated 73.28 for SUS; on the UEQ benchmark scales, they classified excellent (efficiency, dependability, stimulation, and novelty), good (attractiveness), and above-average (perspicuity) and in NPS obtained 62.5%. Moreover, they provided feedback to improve and legitimize that gamification positively interfered in the execution of collaborative practices. In the end, it is possible to suppose that the prototype contributes to the prevention of pressure injuries. In addition, it is possible to adapt it to apply to other pathologies that require continuous health care such as diabetes, mental illness, heart disease, addictions, multiple sclerosis, cancer, among others, maximizing its purpose.Insulator defect detection is an important task in inspecting overhead transmission lines. However, the surrounding environment is complex, and the detection accuracy of traditional image processing algorithms is low. see more Therefore, insulator defect detection is still mainly performed manually. In order to improve this situation, we proposed an insulator defect detection method called INSU-YOLO based on deep neural networks. Overexposure points in the image will interfere with insulator detection, so we used image augment to reduce noise and extract the edge information of the insulator. Based on an attention mechanism, we introduced a structure called attention-block where the backbone extracts the feature map, and this aims to improve the ability of our method to detect insulators. Insulators have a variety of specifications, and the location and granularity of defects are also different. Therefore, we proposed an adaptive threat estimation method based on the area ratio between the entire insulator and the defect area. In addition, in order to solve the problem of data shortage, we established a dataset called InsuDetSet for model training. Experiments on the InsuDetSet dataset demonstrated that our model outperforms existing state-of-the-art models regarding both the detection box and speed.The prevalent demand for remote data sharing and connectivity has catalysed the development of many wireless network technologies. However, low-power and low-rate wireless network technologies have emerged as the preferred choice (due to cheap procurement and maintenance cost, efficiency, and adaptability). Currently, these groups of wireless networks are adopted in homes, health, and business sectors. The increase in existing WSNs has resulted in the incompatibility of wireless network protocols and poses a problem that results in high acquisition or maintenance costs, increased complexity, reliability inadequacies in some instances, lack of uniformity within similar standards, and high energy consumption. To address this problem, we develop a novel machine-to-machine software-based brokerage application (known as JosNet) for interoperability and integration between Bluetooth LE, Zigbee, and Thread wireless network technologies. JosNet allows one network protocol to exchange data packets or commands with each other. In this paper, we present a novel working network brokerage model for a one-to-one network protocol to communication (e.g., from Zigbee to Bluetooth) or one-to-many network protocol communication (e.g., from Bluetooth to Zigbee, Thread, etc.) to securely send messages in a large-scale routing process for short or long-range connections. We also present a large-scale implementation of JosNet using a routing table for large areas. The results show an industry standard performance for end-to-end latency time and throughput.The paper presents the developed fiber-optic sensors for monitoring pressure measurement on the elements of mine supports. The sudden destruction of the support leads to the collapse of the mine workings and poses a serious threat to the life and safety of underground workers. A fiber-optic system for monitoring changes in pressures on the elements of mine supports will increase the share of mining automation and reduce the share of manual labor, as well as eliminate measurement errors associated with the human factor. Systematic monitoring of the state of the working elements of the support will allow timely tracking of their deformations caused by an increase in rock pressure on them. Implementation of the system at mining enterprises will expand the use of digital technologies in mining. Timely warning of a mine collapse threat will significantly increase the level of safe mining operations, as well as reduce the cost of supporting mine workings, since elimination of the consequences of destruction is associated with significant material costs.