Emerging autonomous intersection management systems control the entry order and trajectory for connected and autonomous vehicles ready to traverse a road intersection. They aim to compute trajectories that are safe an...
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The formation of 2D lateral heterostructures in rippled MoS2 and similar transition metal dichalcogenides (TMDs) is studied using density functional theory. Compression of rippled TMDs beyond a threshold compression l...
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The formation of 2D lateral heterostructures in rippled MoS2 and similar transition metal dichalcogenides (TMDs) is studied using density functional theory. Compression of rippled TMDs beyond a threshold compression leads to the formation of a flat valence band associated with strongly localized holes. The implications for exciton manipulation and the emergence of one-dimensional heavy fermion behavior are discussed.
In this work, a method to improve multiple-input-multiple-output (MIMO) antenna system channel capacity based on S-parameter phase difference is proposed. Theoretical derivation and numerical analysis show that the 90...
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High precision and reliable wind speed forecasting have become a challenge for *** events,namely,strong winds,thunderstorms,and tornadoes,along with large hail,are natural calamities that disturb daily *** accurate pr...
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High precision and reliable wind speed forecasting have become a challenge for *** events,namely,strong winds,thunderstorms,and tornadoes,along with large hail,are natural calamities that disturb daily *** accurate prediction of wind speed and overcoming its uncertainty of change,several prediction approaches have been presented over the last few *** wind speed series have higher volatility and nonlinearity,it is urgent to present cutting-edge artificial intelligence(AI)*** this aspect,this paper presents an intelligent wind speed prediction using chicken swarm optimization with the hybrid deep learning(IWSP-CSODL)*** presented IWSP-CSODL model estimates the wind speed using a hybrid deep learning and hyperparameter *** the presented IWSP-CSODL model,the prediction process is performed via a convolutional neural network(CNN)based long short-term memory with autoencoder(CBLSTMAE)*** optimally modify the hyperparameters related to the CBLSTMAE model,the chicken swarm optimization(CSO)algorithm is utilized and thereby reduces the mean square error(MSE).The experimental validation of the IWSP-CSODL model is tested using wind series data under three distinct *** comparative study pointed out the better outcomes of the IWSP-CSODL model over other recent wind speed prediction models.
One of the many components of a vehicle is the lamp system. Beyond lamp functions such as DRL (Daytime Running Light) and CHMSL (Center High Mount Stop Light), vehicle developers are applying ADB (Adaptive Driving Bea...
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This paper describes a test setup to support the development of a bi-directional acoustic communication link relying on adaptive transceivers. The physical layer relies on the JANUS protocol for discovery of new nodes...
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It might be challenging to choose the best text preprocessing strategy in the field of natural language processing (NLP) due to the variety of techniques available. Given the popularity of transformer models, we wonde...
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The performance of object detection in road-driving scenarios is critically important but often hindered by challenges such as occlusion, time-of-day changes (e.g., day and night), and adverse weather conditions (e.g....
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One of the universe's most mysterious things is still black holes, due to their enormous gravity. Black holes are cosmic giants with enormous gravitational force that have event horizons beyond which light cannot ...
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