Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

Breast cancer is highlighted in recent research as one of the most prevalent types of cancer. Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. Grading breast cancer properly, especially evaluating nuclear atypia, is difficult owing to faults and inconsistencies in slide preparation and the intricate nature of tissue patterns. This work explores the capability of deep learning to extract characteristics from histopathology photos of breast cancer. The research introduces a new method called SMOTE-based Convolut

Continual learning on edge platforms remains challenging because recurrent networks depend on energy-intensive training procedures and frequent data movement that are impractical for embedded deployments. This work introduces M2RU, a mixed-signal architecture that implements the minion recurrent unit for efficient temporal processing with on-chip continual learning. The architecture integrates weighted-bit streaming, which enables multi-bit digital inputs to be processed in crossbars without high-resolution conversion, and an experience replay mechanism that stabilizes learning under domain shifts. M2RU achieves ∼13 GOPS at 16.76 mW, corresponding to 776 GOPS per watt, and maintains accuracy within 5 percent of software baselines on seque

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

The molluscicidal effects of herbicide 2, 4-D were studied against tow species of freshwater snail Bulinus truncatus and Melanopsis nodosa by short term experiments. Calculated values of lethal concentrations (LC50 and LC100) were maid to two spices for different period of time 24hr, 48hr, 72hr and 96hr. The study had showed that the herbicide 2, 4-D was toxic against the tow species. The toxicity of the herbicide was low or unknown in low concentrations in the first period of exposure 24and 48hr to two spices but it increase gradually with increase period of exposure. The spice of B.truncatus was more tolerant than the M.nodosa. All the individual of M nodosa was death while in B.truncatus the complete death was not appear until finish the

This study was done to find a cheap, available and ecofriendly materials that can remove eosin y dye from aqueous solutions by adsorption in this study, two adsorbent materials were used, the shells of fresh water clam (Cabicula fluminea) and walnut shells. To make a comparison between the two adsorbents, five experiments were conducted. First, the effects of the contact time, here the nut shell removed the dye quickly, while the C. flumina need more contact time to remove the dye. Second, the effects of adsorbent weight were examined. The nut shell was very promising and for all used adsorbent weight, the R% ranged from 94.87 to 99.29. However C. fluminea was less effective in removing the dye with R% ranged from 47.59 to 55.39. The thi

Sarcasm is conceders one patterns of undesirable communication, which causes social problems in humans relationships because of the contradictory verbal and nonverbal expressions is known sarcasm may defined , statements with intent to belittle others in different situations, dealing with the individual deliberately, to diminish the will or overwhelmed by the recipe stupid, which generate a reaction when a person listener, raising the intentions of ridicule and undermine it, and this may happen is different from the irony interest increased in sarcasm since the development of scientists "Watzlawick '" and Bevin "Jackson's" in 1967 theory interactive and considered the sarcasm one interaction patterns in the social relationship, which use

In this paper, a novel flow control strategy which is the inlet throttled pump was used to design an angular velocity control system for rotary actuator. Inlet throttled systems have good performance in addition to their high efficiency compared to traditional valve controlled systems. The flow in the proposed system is adjusted by a valve that is positioned at the pump inlet with the purpose of reducing the energy loses across the valve. This regulated flow is used then to control the actuator angular velocity. The system was modeled and the open loop stability and performance were studied. In order to improve the system performance, Robust-Proportional-Integral-Derivative (RPID) and structured singular value (M@#@) controllers have been d

PID (proportional-integral-derivative) and Mu controllers are widely used in electro-hydraulic servo systems due to their effectiveness and ease of implementation. This paper explores using particle swarm optimization (PSO) for tuning traditional and robust PID controllers, along with D-K iteration for Mu controller tuning. Three controller types: conventional PID (CPID), robust PID (RPID), and structured singular value controllers are developed, while analyzing multiplicative uncertainty with six uncertain coefficients. Their findings indicated that both PID (CPID and RPID) and Mu controllers maintained system stability. Notably, the Mu controller can handle coefficient uncertainty without a pure integral term, while the RPID controller de