There are currently no effective take-home jaw motion tracking devices to monitor the symptoms in temporomandibular joint disorder (TMD). Existing methods consist of bulky lab equipment that lack a standard for TMD di...
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We report on excellent frequency stability (Allan deviation, or ADEV) down to ~0.1ppb-level measured by operating an aluminum nitride on silicon (AlN/Si) dual-ring bulk acoustic wave (BAW) MEMS resonator in three sche...
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A state-dependent discrete memoryless multiple access channel is considered to model an integrated sensing and communication system, where two transmitters wish to convey messages to a receiver while simultaneously es...
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This paper presents a communication emulation model for enhancing the efficiency of multi-microgrid (MMG) networks, employing Network Simulator 3 (ns3). MMG systems require robust communication frameworks for coordina...
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ISBN:
(数字)9798331520182
ISBN:
(纸本)9798331520199
This paper presents a communication emulation model for enhancing the efficiency of multi-microgrid (MMG) networks, employing Network Simulator 3 (ns3). MMG systems require robust communication frameworks for coordination, particularly under varying traffic conditions. The introduced model accommodates multiple local area networks (LANs) that support efficient communication across multiple autonomous AC microgrids. The developed model facilitates seamless bidirectional information exchange between the microgrids' local controllers and the MMG control center (MMGCC), employing TCP/IP protocol to ensure high data transmission integrity and low latency. A detailed design in C++ is demonstrated, including the configuration of the communication nodes, topology, communication links, and quality of service (QoS) analysis. The network performance is rigorously assessed across low and high traffic conditions, with performance metrics such as throughput, delay, and percentage packet loss at each node. Results confirm the effectiveness of the introduced model in sustaining minimal packet loss, high throughput, and low delays under dynamic operating scenarios. These findings establish the developed model as a viable solution for meeting the real-time communication requirements of MMG energy management systems.
Effective energy storage system (ESS) management is critical for enhancing the performance of standalone DC microgrids, particularly when integrating renewable energy sources such as photovoltaic (PV) or wind systems....
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ISBN:
(数字)9798331520182
ISBN:
(纸本)9798331520199
Effective energy storage system (ESS) management is critical for enhancing the performance of standalone DC microgrids, particularly when integrating renewable energy sources such as photovoltaic (PV) or wind systems. This research describes a new hybrid control technique to improve DC microgrid operations' efficiency and resiliency, especially when handling critical loads. This research presents a hybrid closed-loop control technique that uses Recurrent Neural Networks (RNNs) and Proportional-Integral (PI) controllers to address the complex issues of dynamic load situations and transient disturbances. The RNN evaluates voltage errors to generate accurate reference currents, which the PI controllers then adjust to improve the performance of the bidirectional converter. Unlike standard PI-PI controls, our hybrid approach is particularly effective at regulating pulsed power loads (PPLs) and enhancing system response to transitory situations. The experimental results show that the RNN-PI control scheme significantly improves voltage regulation and transient responsiveness, exceeding conventional performance and resilience techniques. This approach provides a convincing solution for enhancing microgrid systems' stability and efficiency in various real-world applications.
Animal size impacts locomotion, due to its effect on the influence of gravity, inertia, and an animal’s internal elasticity and damping. We are developing a cat robot to further explore the impact of these four chara...
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This study presents a new machine learning algorithm, named Chemical Environment Graph Neural Network (ChemGNN), designed to accelerate materials property prediction and advance new materials discovery. Graphitic carb...
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This survey provides a comprehensive overview of recent emerging technologies in artificial intelligence (AI) applied to the Internet of Things (IoT), highlighting their significance and applications across various do...
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This paper presents an optimized design approach for sub-harmonic synchronous machines (SHSMs) to minimize torque ripple and improve performance for high-power electric vehicle applications. The proposed design incorp...
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Mammalian locomotion is a complex behavior arising from interaction between neural and biomechanical systems, driven by rhythmic activity originating in the spinal cord. Although it has been extensively studied, the s...
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