It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major instability drivers, SHAP analysis improved openness for operators. To our knowledge, this is the first framework that ensures predictive accuracy, real-time corrective control, hardware feasibility, and interpretability simultaneously, as compared to ten other cutting-edge approaches. These results suggest the promise of integrated AI–MPC–FPGA techniques for dependable and transparent smart grid operations.
The development of new building materials, able of absorbing more energy is an active research area. Engineering Cementitious Composite (ECC) is a class of super-elastic fiberreinforced cement composites characterized by high ductility and tight crack width control. The use of bendable concrete produced from Portland Limestone Cement (PLC) may lead to an interest in new concrete mixes. Impact results of bendable concrete reinforced with steel mesh and polymer fibers will provide data for the use of this concrete in areas subject to impact loading. The experimental part consisted of compressive strength and impact resistance tests along with a result comparison with unreinforced concrete. Concrete samples, with dimensions of 100×
... Show MoreIn recent days, the escalating need to seamlessly transfer data traffic without discontinuities across the Internet network has exerted immense pressure on the capacity of these networks. Consequently, this surge in demand has resulted in the disruption of traffic flow continuity. Despite the emergence of intelligent networking technologies such as software-defined networking, network cloudification, and network function virtualization, they still need to improve their performance. Our proposal provides a novel solution to tackle traffic flow continuity by controlling the selected packet header bits (Differentiated Services Code Point (DSCP)) that govern the traffic flow priority. By setting the DSCP bits, we can determine the appropriate p
... Show MoreIn this paper, two new simple, fast and efficient block matching algorithms are introduced, both methods begins blocks matching process from the image center block and moves across the blocks toward image boundaries. With each block, its motion vector is initialized using linear prediction that depending on the motion vectors of its neighbor blocks that are already scanned and their motion vectors are assessed. Also, a hybrid mechanism is introduced, it depends on mixing the proposed two predictive mechanisms with Exhaustive Search (ES) mechanism in order to gain matching accuracy near or similar to ES but with Search Time ST less than 80% of the ES. Also, it offers more control capability to reduce the search errors. The experimental tests
... Show MoreZiegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio
... Show MoreMultilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated d
Among many problems that reduced the performance of the network, especially Wide Area Network, congestion is one of these, which is caused when traffic request reaches or exceeds the available capacity of a route, resulting in blocking and less throughput per unit time. Congestion management attributes try to manage such cases. The work presented in this paper deals with an important issue that is the Quality of Service (QoS) techniques. QoS is the combination effect on service level, which locates the user's degree of contentment of the service. In this paper, packet schedulers (FIFO, WFQ, CQ and PQ) were implemented and evaluated under different applications with different priorities. The results show that WFQ scheduler gives acceptable r
... Show MoreWellbore instability problems cause nonproductive time, especially during drilling operations in the shale formations. These problems include stuck pipe, caving, lost circulation, and the tight hole, requiring more time to treat and therefore additional costs. The extensive hole collapse problem is considered one of the main challenges experienced when drilling in the Zubair shale formation. In turn, it is caused by nonproductive time and increasing well drilling expenditure. In this study, geomechanical modeling was used to determine a suitable mud weight window to overpass these problems and improve drilling performance for well development. Three failure criteria, including Mohr–Coulomb, modifie
The aim of this research is to compare traditional and modern methods to obtain the optimal solution using dynamic programming and intelligent algorithms to solve the problems of project management.
It shows the possible ways in which these problems can be addressed, drawing on a schedule of interrelated and sequential activities And clarifies the relationships between the activities to determine the beginning and end of each activity and determine the duration and cost of the total project and estimate the times used by each activity and determine the objectives sought by the project through planning, implementation and monitoring to maintain the budget assessed
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