Macular edema, diabetic retinopathy, and other apparent microvascular abnormalities in the human retina are common consequences of diabetes. The primary cause of blindness in the past ten years, diabetic retinopathy (...
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In the era of big data, traditional data trading methods designed for one-time queries on static databases fail to meet the demands of continuous query-based trading on streaming data, often resulting in repeated and ...
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This paper proposes a voltage source converter (VSC) -based AC-DC hybrid distribution system (HDS) resilient model to mitigate power outages caused by wildfires. Before a wildfire happens, the public-safety power shut...
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This paper proposes a voltage source converter (VSC) -based AC-DC hybrid distribution system (HDS) resilient model to mitigate power outages caused by wildfires. Before a wildfire happens, the public-safety power shutoff (PSPS) strategy is applied to actively cut some vulnerable lines which may easily cause wildfires, and reinforce some lines that are connected to critical loads. To mitigate load shedding caused by active line disconnection in the PSPS strategy, network reconfiguration is applied before the wildfire occurrence. During the restoration period, repair crews (RCs) repair faulted lines, and network reconfiguration is also taken into consideration in the recovery strategy to pick up critical loads. Since there exists possible errors in the wildfire prediction, several different scenarios of wildfire occurrence have been taken into consideration, leading to the proposition of a stochastic multi-period resilient model for the VSC-based AC-DC HDS. To accelerate the computational performance, a progressive hedging algorithm has been applied to solve the stochastic model which can be written as a mixed-integer linear program. The proposed model is verified on a 106-bus AC-DC HDS under wildfire conditions, and the result shows the proposed model not only can improve the system resilience but also accelerate computational speed.
Aims: The aim of this paper is to develop a new, simple equation for deep spherical indentations. Background: The Hertzian theory is the most widely applied mathematical tool when testing soft materials because it pro...
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The performances of microwave and radio frequency (RF) devices can be characterized through their equivalent circuits by observing each of its constituent elements. The use of equivalent circuit is recently becoming a...
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This research investigates the development of an EOG (electrooculography)-based wheelchair controlled by eye movements, including blinks and glances. The system leverages peak signal features for conscious blinking (o...
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Generative design is an AI-driven process to explore all the possible design variants, it mimics nature's evolutionary approach to create an optimised final design. Generative design and additive manufacturing are...
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The most common cause of blindness in the world is glaucoma. It can lead to a decline in eyesight and quality of life if not addressed within the stipulated time. In computer vision, convolutional neural networks (CNN...
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This study aims at exploring the use of internet of things technology and data analytics in the field of supply chain management. Using a range of software tools, including Apache Kafka, Apache NiFi, Python libraries ...
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This study focuses on developing a predictive model for late deliveries in the supply chain, using the Data Co Supply Chain dataset. It involves data cleaning, visualization, and training various machine learning algo...
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