Improving the initialization speed for long-range NRTK in network solution mode

Initialization speed is one of the most important factors in network real time kinematic (NRTK) performance. Owing to the low correlation among the error s     

Effects of Undercooling and Transformation Time on Microstructure and Strength of Fe–C–Mn–Si Superbainitic Steel

Strength of Materials - A metallographic method, dilatometry, and X-ray diffraction were applied to investigate the effects of undercooling and holding time on bainitic transformation,...     

Continuation methods for approximate large scale object sequencing

Machine Learning - We propose a set of highly scalable algorithms for the combinatorial data analysis problem of seriating similarity matrices. Seriation consists of finding a permutation of data...     

Fabrication of hierarchical PANI@W-type barium hexaferrite composites for highly efficient microwave absorption

Hexagonal barium ferries is a promising and efficient microwave (MW) absorbing material, but the low dielectric loss and poor conductivity have limited their extensive applications. In this work, a simple tactic of coating conductive polymer PANI on hexaferrite BaCo₂Fe₁₆O₂₇ is presented, wherein the dielectric properties are customized, and more significantly, the electromagnetic loss is greatly enhanced. As displayed from structural characterizations, PANI were coated equably on the surface of hexaferrite grains by an in-situ polymerization process. The outcomes exhibit the as-prepared PANI@hexaferrite composite has remarkable electromagnetic wave absorption capacity. When the thickness is 6.0 mm, the minimal RL of ?40.4 dB was achieved at 2.9 GHz. The effective absorption bandwidth (RL < ?20 dB) of 0.65 GHz, 0.53 GHz, 0.65 GHz, 0.52 GHz, 0.46 GHz and 0.39 GHz was achieved separately when the thickness ranges from 4 to 9 mm. The highly efficient MW absorbing performance of PANI@hexaferrite composite were the consequence of multiple loss mechanisms and perfect impedance matching. It is demonstrated that the PANI@hexaferrite composite with excellent MW absorption performance is expected to be potential MW absorbers for extensive applications.     

RLPAS: Reinforcement Learning-based Proactive Auto-Scaler for Resource Provisioning in Cloud Environment

Mobile Networks and Applications - Public cloud system offers Infrastructure-as-a-Service (IaaS) to deliver the computational resources on demand. Resource requirements of a cloud environment are...