Because imitation learning relies on human demonstrations in hard-to-simulate settings, the inclusion of force control in this method has resulted in a shortage of training data, even with a simple change in speed. Al...
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The task of image anomaly detection (IAD) aims to identify deviations from normality in image data. These anomalies are patterns that deviate significantly from what the IAD model has learned from the data during trai...
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Onshore wind farms present a highly promising solution for hydrogen production to boost renewable energy integration, support decarbonization, and enhance energy security. This study offers a detailed numerical model ...
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ISBN:
(数字)9798331529987
ISBN:
(纸本)9798331529994
Onshore wind farms present a highly promising solution for hydrogen production to boost renewable energy integration, support decarbonization, and enhance energy security. This study offers a detailed numerical model to evaluate the potential for hydrogen production using onshore wind power in an arid coastal community located in the southern region of the Aqaba Gulf, Saudi Arabia. The proposed model emulates formulas to determine electrolyzer plant sizing, wind output power, and green hydrogen production. The goal is to develop an optimal hydrogen production plant using high wind resources, whilst assessing its economic viability, reducing production costs, and minimizing CO2 emissions. The results indicate that the optimal Onshore Wind-Hydrogen System (OWHS) comprises 26 wind turbines (WTs), each with a rated capacity of 6.15 MW, alongside Alkaline Electrolyzers with a total capacity of 120 MW and a hydrogen storage capacity of 300 tonnes. The subsidiary electricity needs and hydrogen demand are efficiently met with 160 MW of wind generation capacity, with minimal capacity shortages. The alkaline electrolyzers used have a total rated capacity of 120 MW and can operate for 7,335 hours per year, producing 8,214,152 kg of green hydrogen annually. The OWHS can produce hydrogen at a cost of 5.26 $/kg, which aligns with the global range of 4$ to 6$ per kilogram. Additionally, the system achieves CO2 mitigation of 3,344 metric tons, resulting in a net carbon credit value of 133.75$. The obtained outcomes highlight the potential advantages and cost savings of incorporating green hydrogen production into Aqaba Gulf wind projects for Saudi Arabia’s coastal community.
To achieve the goal of net zero by 2050, carbon dioxide emissions must be reduced using carbon–neutral fuels, and methanol is a feasible choice for gas turbines, IC engines, and furnaces. Methanol can be prepared by ...
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We suggest new CO2 absorption processes with biphasic phase separation type for reducing consumption energy. the CO2-rich solution liquid was separated hydrophilic liquid and hydrophobic liquid. In this work, we studi...
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Target tracking in infrared images is actively researched in computer vision. Unlike RGB images, infrared images rely on a single channel of thermal signals, making them vulnerable to issues such as non-uniform illumi...
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ISBN:
(数字)9798331520403
ISBN:
(纸本)9798331520410
Target tracking in infrared images is actively researched in computer vision. Unlike RGB images, infrared images rely on a single channel of thermal signals, making them vulnerable to issues such as non-uniform illumination and noise. In this study, we propose integrating CLAHE (Contrast-Limited Adaptive Histogram Equalization), a preprocessing technique, into the SiamRPN framework, a widely used Siamese network-based tracker. CLAHE enhances local contrast while maintaining computational efficiency, enabling robust tracking, even in resource-constrained environments. The performance of the proposed method was evaluated using challenging subsets of the LSOTB-TIR dataset, selected to represent conditions where standard models typically struggle. Experimental results demonstrate that the CLAHE-enhanced SiamRPN achieves significant improvements in accuracy and robustness compared to the baseline model, particularly in environments with low contrast and complex backgrounds. These findings suggest that CLAHE can be a practical solution for improving performance in environments with limited computational resources.
This study delves into the utilization of Generative Adversarial Networks (GANs) for generating subject-specific time series sensor data, offering an innovative alternative to traditional metamodel-based simulations. ...
ISBN:
(纸本)9798350369663
This study delves into the utilization of Generative Adversarial Networks (GANs) for generating subject-specific time series sensor data, offering an innovative alternative to traditional metamodel-based simulations. We undertake an in-depth analysis of DoppelGANger, a prominent GAN variant for time series data and metadata generation, evaluating its efficiency and efficacy. The sensor data for this investigation was sourced from the National Health and Nutrition Examination Survey, which served as the foundational training set. We scrutinized the synthesized sensor data corresponding to various physical attributes, focusing on the temporal and multi-dimensional statistical properties. Our empirical findings underscore the potential of GANs to adeptly capture the time-dependent correlations and the intricate statistical characteristics inherent in multi-dimensional data. This insight into GANs' capabilities is a crucial step towards more sophisticated synthetic data generation, with significant implications for future applications in wearable technology and personalized health monitoring systems.
Melanoma is a malignant form of cancer that affects the skin and has a particularly high mortality rate, so it requires early detection to increase the level of safety for users. Diagnosis and detection of skin cancer...
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Controllers act as a bridge between the operator and the system, allowing the operator to communicate with the system as if it were a human. In other words, the controller is like the thinking brain of an industrial p...
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ISBN:
(数字)9798350377170
ISBN:
(纸本)9798350377187
Controllers act as a bridge between the operator and the system, allowing the operator to communicate with the system as if it were a human. In other words, the controller is like the thinking brain of an industrial process. A controller communicates all the commands that an expert wants to apply to the system to follow its standard flow process and ultimately achieve the desired response. When industrial processes are left alone and without a controller in the control loop, they typically do not give satisfactory responses in terms of transient or steady-state characteristics. Therefore, the selection and programming of an appropriate controller is one of the most important steps in an industrial process. One of the most widely used and well-known controllers is the PID controller, whose gains are often determined experimentally or through trial and error. However, finding the optimal gains is always a challenge. In this study, for the first time, the optimal gains of the PID controller are determined using Lion Optimization Algorithm (LOA). This research has introduced a systematic and efficient approach to achieving optimal control of mechatronic systems.
In this paper we take a combinatorial approach to the problem of list-decoding, which allows us to determine the precise relation (up to the exact constant) between the decoding radius, list size, and code rate. We pr...
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