Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, ...
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As the integration of Variable Renewable Energy (VRE) generators into power systems increases, there is a potential decrease in overall system reliability, particularly in terms of stability. This research suggests th...
As the integration of Variable Renewable Energy (VRE) generators into power systems increases, there is a potential decrease in overall system reliability, particularly in terms of stability. This research suggests the integration of a Battery Energy Storage System (BESS) into a power system with Variable Renewable Energy sources, such as a utility-scale Photovoltaic (PV) plant, to accelerate the damping of post-fault oscillations following a short-circuit disturbance. The objective is for a Power Oscillation Damping (POD) within the PV plant to address post-fault oscillations within a specific timeframe. The POD in the PV plant is designed to supply additional active and reactive power, responding to the system's demands after a disturbance. The addition of BESS to the system is anticipated to enhance the time required for the system to achieve a stable state, resulting in quicker system stabilization. Simulations conducted through PSCAD software can effectively depict the post-fault conditions of short-circuit disturbances, considering the impact of the integrated BESS.
This paper discusses West Kalimantan's dependency on imported electricity and fossil fuels and advocates for integrating renewable energy sources, especially solar power. With abundant solar resources and its equa...
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ISBN:
(数字)9798350376067
ISBN:
(纸本)9798350376074
This paper discusses West Kalimantan's dependency on imported electricity and fossil fuels and advocates for integrating renewable energy sources, especially solar power. With abundant solar resources and its equatorial location, West Kalimantan presents a significant solar PV generation opportunity. However, its dependence on imported electricity from the ASEAN Grid initiative poses risks to energy security. By promoting solar power as an alternative energy source and reducing reliance on fossil fuels, the paper aims to improve energy independence and sustainability. Integrating solar PV requires assessing frequency stability to ensure system resilience. Moreover, the interconnection between the two grids enhances system resilience and facilitates renewable energy integration. In summary, integrating solar PV power plants into the West Kalimantan system aims to decrease dependence on electricity imports from Sarawak while preserving the system's frequency stability.
Integrating wind turbine generation (WTG) into the power grid presents challenges due to their variable and unpredictable output, creating instability. The intermittent nature of wind power and the reduced inertia of ...
Integrating wind turbine generation (WTG) into the power grid presents challenges due to their variable and unpredictable output, creating instability. The intermittent nature of wind power and the reduced inertia of wind turbines pose significant challenges to maintaining power system stability, especially during grid faults and transient events. Intermittency can impact the electrical grid's stability and requires additional grid balancing and energy storage measures. This study proposes a Power Oscillation Damping (POD) control scheme integrated with battery energy to enhance WTG stability following grid faults. The proposed scheme combines a POD controller for WTG and a battery controller, demonstrating faster oscillation damping than a WTG without batteries. During damping control, the scheme prioritizes active power control of POD, utilizing the wind turbine's kinetic energy. Simultaneously, the reactive power control of POD adjusts based on the synchronous generator's rotational speed to maintain voltage stability. Feedback for both control loops is derived from the nearest synchronous generator, ensuring coordinated and responsive control. Adding a battery into the control scheme helps to smooth out power fluctuations and enhance stability. Therefore, it is possible to compensate for the intermittency of wind power and voltage drop after short-circuit events through various measures, such as advanced control systems and battery power. The effectiveness of this proposed control scheme, with the added integration of Battery Energy, is validated through the PSCAD simulator involving a short-circuit fault in a two-area power system. Results demonstrate a notable improvement in power system stability, particularly after grid faults.
Universities can employ information technology as one means of achieving their goals and objectives. Universities can get advantages from information technology, such as effective resource management and information m...
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In HV equipment, the most critical and valuable components used is transformers. Power transformers should go through standard diagnostic tests to identify deterioration or to avoid the emergence of defects that might...
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Providing robust prognosis predictions for cancers with limited data samples remains a challenge for precision oncology. In this study, we propose a novel approach that combines multi-task learning (MTL) and graph neu...
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ISBN:
(数字)9798350371499
ISBN:
(纸本)9798350371505
Providing robust prognosis predictions for cancers with limited data samples remains a challenge for precision oncology. In this study, we propose a novel approach that combines multi-task learning (MTL) and graph neural networks (GNNs) to address this issue. By representing gene-gene interactions as a graph network, our approach leverages multi-task learning to effectively capture the relationships of genes relevant to the oncogenesis and progression of breast, lung, and colon cancer. We demonstrate that our approach improves the cancer prognosis prediction for cancers with fewer samples, such as colon adenocarcinoma, by leveraging the shared gene-gene interactions across different cancer types, obtaining increases in the area under the precision-recall curve (AUPRC) of 24%. Our work contributes to the field of smart healthcare by demonstrating the potential of MTL and GNNs for enhancing cancer prognosis prediction, even with limited data samples.
E-learning environments are increasingly harnessing large language models (LLMs) like GPT-3.5 and GPT-4 for tailored educational support. This study introduces an approach that integrates dynamic knowledge graphs with...
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This paper addresses the reference tracking control problem for Medical Cyber-Physical Systems (MCPS). The control theory is employed to guarantee the suitable concentration of drugs in the body of patients to guarant...
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As the need for achieving optimal performance in prediction models, several recent and complex models have been developed. However, many of these models operate as black boxes, providing little insight into their pred...
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ISBN:
(数字)9798350376210
ISBN:
(纸本)9798350376227
As the need for achieving optimal performance in prediction models, several recent and complex models have been developed. However, many of these models operate as black boxes, providing little insight into their predictive results. In recent years, three gradient-boosting methods based on Decision Trees have been recommended, i.e., XGBoost, CatBoost, and LightGBM. These methods have proven to deliver competitive performance with fast training times. Nevertheless, in critical domains like security, there is a growing need for increased transparency among stakeholders. One pressing concern in the security field is the proliferation of phishing websites. To address this issue, we propose an explainable machine learning-based approach using gradient-boosting methods with hyperparameter optimization on three phishing website datasets. Our best methods surpass the state-of-the-art phishing website detection methods, achieving accuracy rates of 97.45%, 99.16%, and $\mathbf{9 7. 8 5 \%}$ for the UCI (2015), Mendeley (2018), and Mendeley (2020) datasets, respectively. Subsequently, we implement posthoc explainability using SHAP and LIME for the selected dataset. The experimental results indicate that three features, i.e., length_url, directory_length, and time_domain_activation, are consistently identified as the most influential features in the dataset. Moreover, our proposed approach demonstrates promising results for detecting phishing websites with both high accuracy and explainability.
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