Spatial modulation Orthogonal Frequency Division Multiplexing (SM OFDM) is a newly developed transmission technique that has been proposed as an alternative for multiple input multiple output (MIMO)-OFDM transmission....
详细信息
This paper presents a controller for fast and ultrafast electric vehicle(EV)charging *** affecting the charging efficiency,the proposed controller enables the charger to provide support to the interconnection voltage ...
详细信息
This paper presents a controller for fast and ultrafast electric vehicle(EV)charging *** affecting the charging efficiency,the proposed controller enables the charger to provide support to the interconnection voltage to counter and damp its *** solutions are either hardware-based such as using supercapacitors and flywheels which increase the cost and bulkiness of the charging station,or software-based such as P/V droop methods which are still unable to provide a robust and strong voltage *** paper proposes an emulated supercapacitor concept in the control system of the ultra-fast EV charger in an islanded DC ***,it converts the EV from a static load to a bus voltage supportive load,leading to reduced bus voltage oscillations during single and multiple ultra-fast EV charging operations,and rides through and provides supports during extreme external *** analysis and design guidelines of the proposed controller are presented,and its effectiveness and improved performance compared with conventional techniques are shown for different case studies.
Neural decoding plays a vital role in the interaction between the brain and the outside world. Our task in this paper is to decode the movement track of a finger directly based on the neural data. Existing neural deco...
详细信息
1 Introduction A related study called community search,whose target is to find dense subgraphs containing the given node,has drawn a growing amount of attention recently[1].To explore the higher-order structure of com...
详细信息
1 Introduction A related study called community search,whose target is to find dense subgraphs containing the given node,has drawn a growing amount of attention recently[1].To explore the higher-order structure of complex networks,truss-based community search methods[2]have been ***,the truss-based hypergraph constructed from the original graph is frequently fragmented and consists of numerous subgraphs and isolated nodes[3],which boils down to the fact that these methods often pay only attention to the truss connections but ignore the lower-order connectivity of the original graph.
The metaverse is a new trend in virtual reality applications, and data storage and management commonly rely on distributed storage systems. The integrity of the stored data has become a key concern in the metaverse. F...
详细信息
Modeling and controlling complex spatiotemporal dynamical systems driven by partial differential equations (PDEs) often necessitate dimensionality reduction techniques to construct lower-order models for computational...
详细信息
Over one billion people worldwide are affected with neurological disorders and their economic impact is approximately $800 billion annually, which constitutes major medical challenge. Using neuromodulation systems cur...
详细信息
ISBN:
(纸本)9798331543617
Over one billion people worldwide are affected with neurological disorders and their economic impact is approximately $800 billion annually, which constitutes major medical challenge. Using neuromodulation systems currently available suffers from sensitivity, reaction time as well as energy consumption. The proposal in this research is to address these major issues in closed loop neuromodulation by using a Quantum enhanced Spiking Neural Network (QESNN) architecture. This paper represents the interfacing of two major fields: quantum sensing and neuromorphic computing. The QESNN architecture comprises three core components: This is implemented as an array of quantum sensors, a quantum classical hybrid interface, and a spiking neural network (SNN). Taking advantage of quantum superposition and entanglement principles, the quantum sensor array noninvasively images neural activity at the level of single action potentials using NV centers. These sensors work at ambient temperatures, which is unlike superconducting devices. For processing with neuromorphic processing, quantum-classical hybrid converts quantum sensor data into classical signals with advanced signal process such as quantum state estimation and noise reduction. By modeling biological neurons with leaky integrate and fire neurons, the SNN serves as a low power, timed neural dynamics modulation component that emulates biological event driven behavior. A key innovation in our architecture is adaptive thresholding, which dynamically adjusts detection thresholds based on signal distributions, improving sensitivity and reducing false positives by 45.6%. The system also achieves 20-30% higher power efficiency through techniques like adaptive sensor frequency control and low-power processing. Simulation results that show how the QESNN performs better than classical systems with less false positives and greater energy efficiency are presented. A new platform is demonstrated that integrates quantum sensing with neurom
Throughout the globe, transportation is the backbone of every country and a necessity of every human nowadays. Numerous problems (rain, fog, snow, dust, mist, potholes, overspeed, drowsiness of driver, absence of ligh...
详细信息
Multi-modal medical image fusion maximizes the complementary information from diverse modality images by integrating source images. The fused medical image could offer enhanced richness and improved accuracy compared ...
详细信息
Multi-modal medical image fusion maximizes the complementary information from diverse modality images by integrating source images. The fused medical image could offer enhanced richness and improved accuracy compared to the source images. Unfortunately, the existing deep learning-based medical image fusion methods generally rely on convolutional operations, which may not effectively capture global information such as spatial relationships or shape features within and across image modalities. To address this problem, we propose a unified AI-Generated Content (AIGC)-based medical image fusion, termed Cross-Modal Interactive Network (CMINet). The CMINet integrates a recursive transformer with an interactive Convolutional Neural Network. Specifically, the recursive transformer is designed to capture extended spatial and temporal dependencies within modalities, while the interactive CNN aims to extract and merge local features across modalities. Benefiting from cross-modality interaction learning, the proposed method can generate fused images with rich structural and functional information. Additionally, the architecture of the recursive network is structured to reduce parameter count, which could be beneficial for deployment on resource-constrained devices. Comprehensive experiments on multi-model medical images (MRI and CT, MRI and PET, and MRI and SPECT) demonstrate that the proposed method outperforms the state-of-the-art fusion methods subjectively and objectively. IEEE
Die-stacked dynamic random access memory(DRAM)caches are increasingly advocated to bridge the performance gap between the on-chip cache and the main *** fully realize their potential,it is essential to improve DRAM ca...
详细信息
Die-stacked dynamic random access memory(DRAM)caches are increasingly advocated to bridge the performance gap between the on-chip cache and the main *** fully realize their potential,it is essential to improve DRAM cache hit rate and lower its cache hit *** order to take advantage of the high hit-rate of set-association and the low hit latency of direct-mapping at the same time,we propose a partial direct-mapped die-stacked DRAM cache called *** design is motivated by a key observation,i.e.,applying a unified mapping policy to different types of blocks cannot achieve a high cache hit rate and low hit latency *** address this problem,P3DC classifies data blocks into leading blocks and following blocks,and places them at static positions and dynamic positions,respectively,in a unified set-associative *** also propose a replacement policy to balance the miss penalty and the temporal locality of different *** addition,P3DC provides a policy to mitigate cache thrashing due to block type *** results demonstrate that P3DC can reduce the cache hit latency by 20.5%while achieving a similar cache hit rate compared with typical set-associative caches.P3DC improves the instructions per cycle(IPC)by up to 66%(12%on average)compared with the state-of-the-art direct-mapped cache—BEAR,and by up to 19%(6%on average)compared with the tag-data decoupled set-associative cache—DEC-A8.
暂无评论