There has been significant recent progress to reduce the computational effort of static IR drop analysis using neural networks, and modeling as an image-to-image translation task. A crucial issue is lack of sufficient...
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The oil and gas industry is increasingly depending on advanced data analytics to maximize production and reduce costs. Perhaps the greatest difficult issue in this industry is precisely estimating the performance of d...
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Review of laboratory test data is a management focus for compliance laboratories. Using BERT-based intelligent analysis to analyze the laboratory instrument test data can assist laboratory testing personnel to quickly...
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Review of laboratory test data is a management focus for compliance laboratories. Using BERT-based intelligent analysis to analyze the laboratory instrument test data can assist laboratory testing personnel to quickly and accurately obtain the target data. This paper, with high-performance liquid chromatography (HPLC) as an example, applies big data technology and machine learning algorithm to the intelligent analysis and application of instrument test data by reading the output files in combination with the historical data of laboratory management system and business system, to realize the automatic acquisition of instrument test data, which reduces the laboratory labor cost, improves the laboratory test efficiency, optimizes the laboratory test management, and improves the quality control level.
Automation has become a necessity for industries striving to enhance productivity and eliminate errors in the age of Industry 4.0. Automatic bottle filling devices are essential in the beverage sector for precisely fi...
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Effective fault detection and diagnosis can significantly enhance the operational efficiency and reliability of inspection equipment, ensuring the smooth progress of inspection work. To achieve efficient equipment mon...
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High Voltage Direct Current (HVDC) technology based on line commutated converters (LCC) is crucial for integrating large-scale renewable energy and long-distance power transmission. However, high-frequency oscillation...
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Rooftop agriculture for food production and photovoltaic (PV) panels for energy generation are two examples of how urban functional design presents a potential alternative to multi-function urban land-use that may giv...
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Rooftop agriculture for food production and photovoltaic (PV) panels for energy generation are two examples of how urban functional design presents a potential alternative to multi-function urban land-use that may give numerous ecosystem services. In order to find the optimal rooftop usage strategy that takes into account many choice criteria and to comprehend how rooftop solutions affect the layout of urban energy infrastructure, we provide a complete system modeling approach that demonstrates multi-objective optimization of energy systems. With a reduced levelized cost of electricity (LCOE), rooftop photovoltaics have gained considerable traction recently owing to technical, economical, and environmental benefits;this research aims to prove their viability. The suggested PV size and cost factor, taking environmental conditions and shading effects into consideration, were determined using two methods: Quantum Particle Swarm Optimization (PSO) with Q-Learning System. Rooftop photovoltaics system sizing, economic feasibility, and energy efficiency are all affected by the results that are compared. University of Engineering & Technology (UET), a public sector institution, has its main campus in Taxila, where this research was conducted. Situated in northern Pakistan, its appropriate position is advantageous for the research. The lifespan, performance ratio (PR), and decrease of the Rooftop Photovoltaics system's carbon footprint are among the many additional criteria that are examined. Because of this, installing rooftop photovoltaic systems on government buildings is a more sensible and feasible solution.
China is actively promoting the development of renewable energy sources such as wind power and photovoltaic to achieve the goal of "carbon neutrality and carbon peaking". However, renewable energy sources su...
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Many clinical trials have shown the effectiveness of combination therapy over monotherapy in diabetes management. Sitagliptin (SG) and metformin (MF) are the most common combinations for type II diabetes management. T...
Many clinical trials have shown the effectiveness of combination therapy over monotherapy in diabetes management. Sitagliptin (SG) and metformin (MF) are the most common combinations for type II diabetes management. These drugs were combined into one tablet, called Janumet 50/850 (SG/MF). The pharmaceutical industry constantly demands a rapid, simple, sensitive, and valid analytical method for simultaneously determining drugs in pharmaceutical products. Therefore, this study aims to develop an ultraperformance liquid chromatography method for concurrently estimating metformin and sitagliptin in a short run time by applying the response surface methodology. A Box-Behnken design was implemented to study the influence of three independent factors: aqueous phase concentration in the mobile phase (A;5-15%), mobile phase flow rate (B;0.4-1 mL/min), and ammonium formate buffer strength (C;5-20 mM). The dataanalysis showed a significant negative effect of the flow rate on the retention time and peak area. The optimized analytical condition was performed with 15% aqueous phase concentration, a flow rate of 0.52 mL/min, and a buffer strength of five mM. The analytical method was valid per the International conference of Harmonization (ICH) guidelines. SG and MF were separated in a short time run of 2 min. The process was reliable in separating and extracting the drugs from the marketed Janumet tablets at a retention time of 0.73 and 1.36 min for SG and MF, respectively.
Path tracking control is a fundamental technology in autonomous vehicle applications, but it faces significant challenges related to vehicle modeling and external disturbances. In this paper, an improved model-free ad...
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ISBN:
(数字)9798331521950
ISBN:
(纸本)9798331521967
Path tracking control is a fundamental technology in autonomous vehicle applications, but it faces significant challenges related to vehicle modeling and external disturbances. In this paper, an improved model-free adaptive control strategy, leveraging data-driven approaches and gradient descent parameter optimization, is proposed. First, an enhanced lineofsight method is used to generate the desired heading angle, simplifying the multi-dimensional path tracking problem into a more manageable heading angle tracking task. Then, the gradient descent model-free adaptive control strategy is applied, with the core idea of incorporating the gradient descent algorithm in the controller's time-varying parameter update process to achieve optimal control. The effectiveness of the proposed algorithm is validated through simulations, demonstrating its robustness in nonlinear systems and path tracking control scenarios. Comparative analysis with model-based methods highlights the superior stability and adaptability of the approach.
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