As power grids evolve towards smarter, more transparent systems, there is an increasing demand for high-precision, high-reliability, and cost-effective voltage measurement techniques. Unlike traditional contact method...
详细信息
the underwater unmanned vehicle (UUV) has strict requirements for the volume, noise, and dynamic response of the motor propulsion system. therefore, a control algorithm of permanent magnet synchronous motor (PMSM) com...
详细信息
In recent years, the development of household distributed photovoltaics has been rapid, and its unobservable characteristics have brought huge challenges to the planning and control of the power grid and user energy m...
详细信息
After the distributed power supply connects to the new power system, the power grid scheduling is affected by voltage flash during the grid scheduling, resulting in an increase in operating costs of the power grid. It...
详细信息
Intrusion Detection systems (IDSs) have emerged as essential tools for detecting cyber attacks and safeguarding sensitive data. Over time, there has been a shift towards designing IDSs that leverage Federated Learning...
详细信息
ISBN:
(纸本)9798350390797;9789532901351
Intrusion Detection systems (IDSs) have emerged as essential tools for detecting cyber attacks and safeguarding sensitive data. Over time, there has been a shift towards designing IDSs that leverage Federated Learning (FL) methods, enabling them to detect attacks across distributed environments while upholding privacy-preserving manner. Concurrently, selecting the appropriate algorithm for Host execution, ensuring data privacy, low power consumption, and swift execution, has become a promising challenge. Recently, there has been a growing interest in Spike Neural Networks (SNNs) due to their ability to directly generate spikes and closely emulate human brain functions. SNN-based models are optimized to achieve energy efficiency by representing computations through asynchronously generated spikes. To tackle these challenges, we propose a theoretical approach for implementing a Federated Intrusion Detection System (IDS) that gathers data from different geographical locations, based on Neuromorphic computing principles.
the industrial world is undergoing a major transformation as operational technology (OT) and information technology (IT) converge. this trend is being driven by the much faster evolution of IT compared to OT. this pap...
详细信息
In order to effectively screen patients during the COVID-19 pandemic, novel strategies have been required on a global scale. Smart data and the Internet of things (IoT) have proven to be important in this context. the...
详细信息
distributed training crossing multiple computing nodes and accelerators has been the mainstream solution for large model training. Precedent work on distributed deep learning (DDL) training acceleration has focused on...
详细信息
Cache-aware algorithms are based on the fair assumption that requests from the same user need shared data that can be cached locally on the information processing center. So, caching is an effective way to improve per...
详细信息
In recent years, the rapid growth in the number of electric vehicles (EVs) has resulted in significant challenges for power systems in terms of load management. While traditional vehicle-to-grid (V2G) technology can m...
详细信息
暂无评论