431 research outputs found
Utility greedy discrete bit loading for interference limited multi-cell OFDM system
In this contribution we present the solution of the utility greedy discrete bit loading for interference limited multicell OFDM networks. Setting the utility as the sum of consumed power proportions, the algorithm follows greedy way to achieve the maximum throughput of the system. Simulation has shown that the proposed algorithm has better performance and lower complexity than the traditional optimal algorithm. The discussion of the results is provided
Planetary gearbox fault diagnosis using morphological gradient filters
As a key component of rotating machineries, fault diagnosis for planetary gearbox is very difficult compared to the fixed shaft gearbox. It is becoming a hot research topic recent years. Different fault type has different vibration characteristics. Different from the traditional signal analysis methods, morphological gradient filters are used to extract the fault frequencies in this paper. Planetary gearbox experiment signals are used to validate the proposed method
Dual-resolution correspondence networks
We tackle the problem of establishing dense pixel-wise correspondences between a pair of images. In this work, we introduce Dual-Resolution Correspondence Networks (DualRC-Net), to obtain pixel-wise correspondences in a coarse-to-fine manner. DualRC-Net extracts both coarse- and fine- resolution feature maps. The coarse maps are used to produce a full but coarse 4D correlation tensor, which is then refined by a learnable neighbourhood consensus module. The fine-resolution feature maps are used to obtain the final dense correspondences guided by the refined coarse 4D correlation tensor. The selected coarse-resolution matching scores allow the fine-resolution features to focus only on a limited number of possible matches with high confidence. In this way, DualRC-Net dramatically increases matching reliability and localisation accuracy, while avoiding to apply the expensive 4D convolution kernels on fine-resolution feature maps. We comprehensively evaluate our method on large-scale public benchmarks including HPatches, InLoc, and Aachen Day-Night. It achieves the state-of-the-art results on all of them
Equipment Design for Lunar Lander Landing-Impact Test
In order to verify the performance of lunar lander structure, landing-impact test is urgently needed. Moreover, the test equipment is necessary for the test. The functions and the key points of the equipment is presented to satisfy the requirements of the test,and the design scheme is proposed. The composition, the major function and the critical parts' design of the equipment are introduced. By the load test of releasing device and single-beam hoist, and the compatibility test of landing-impact testing system, the rationality and reliability of the equipment is proved
Dual-Resolution Correspondence Networks
We tackle the problem of establishing dense pixel-wise correspondences
between a pair of images. In this work, we introduce Dual-Resolution
Correspondence Networks (DRC-Net), to obtain pixel-wise correspondences in a
coarse-to-fine manner. DRC-Net extracts both coarse- and fine- resolution
feature maps. The coarse maps are used to produce a full but coarse 4D
correlation tensor, which is then refined by a learnable neighbourhood
consensus module. The fine-resolution feature maps are used to obtain the final
dense correspondences guided by the refined coarse 4D correlation tensor. The
selected coarse-resolution matching scores allow the fine-resolution features
to focus only on a limited number of possible matches with high confidence. In
this way, DRC-Net dramatically increases matching reliability and localisation
accuracy, while avoiding to apply the expensive 4D convolution kernels on
fine-resolution feature maps. We comprehensively evaluate our method on
large-scale public benchmarks including HPatches, InLoc, and Aachen Day-Night.
It achieves the state-of-the-art results on all of them
Equipment Design for Lunar Lander Landing-Impact Test
In order to verify the performance of lunar lander structure, landing-impact test is urgently needed. Moreover, the test equipment is necessary for the test. The functions and the key points of the equipment is presented to satisfy the requirements of the test,and the design scheme is proposed. The composition, the major function and the critical parts' design of the equipment are introduced. By the load test of releasing device and single-beam hoist, and the compatibility test of landing-impact testing system, the rationality and reliability of the equipment is proved
Deciphering ion concentration polarization-based electrokinetic molecular concentration at the micro-nanofluidic interface: theoretical limits and scaling laws
The electrokinetic molecular concentration (EMC) effect at the micro-nanofluidic interface, which enables million-fold preconcentration of biomolecules, is one of the most compelling yet least understood nanofluidic phenomena. Despite the tremendous interests in EMC and the substantial efforts devoted, the detailed mechanism of EMC remains an enigma so far owing to its high complexity, which gives rise to the significant scientific controversies outstanding for over a decade and leaves the precise engineering of EMC devices infeasible. We report a series of experimental and theoretical new findings that decipher the mechanism of EMC. We demonstrate the first elucidation of two separate operating regimes of EMC, and establish the first theoretical model that analytically yet concisely describes the system. We further unveil the dramatically different scaling behaviors of EMC in the two regimes, thereby clarifying the long-lasting controversies. We believe this work represents important progress towards the scientific understanding of EMC and related nano-electrokinetic systems, and would enable the rational design and optimization of EMC devices for a variety of applications.National Institutes of Health (U.S.) (Grant No. U19AI109755)National Science Council (China) (Grant No. 11372229)National Science Council (China) (Grant No. 21576130)National Science Council (China) (Grant No. 21490584
Robust Ellipsoid Fitting Using Axial Distance and Combination
In random sample consensus (RANSAC), the problem of ellipsoid fitting can be
formulated as a problem of minimization of point-to-model distance, which is
realized by maximizing model score. Hence, the performance of ellipsoid fitting
is affected by distance metric. In this paper, we proposed a novel distance
metric called the axial distance, which is converted from the algebraic
distance by introducing a scaling factor to solve nongeometric problems of the
algebraic distance. There is complementarity between the axial distance and
Sampson distance because their combination is a stricter metric when
calculating the model score of sample consensus and the weight of the weighted
least squares (WLS) fitting. Subsequently, a novel sample-consensus-based
ellipsoid fitting method is proposed by using the combination between the axial
distance and Sampson distance (CAS). We compare the proposed method with
several representative fitting methods through experiments on synthetic and
real datasets. The results show that the proposed method has a higher
robustness against outliers, consistently high accuracy, and a speed close to
that of the method based on sample consensus.Comment: 13 page
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