A two-stage gasification has been proven as an effective and robust approach for converting low-valued and/or highly heterogeneous materials i.e. waste, into hydrogen syngas due to its tight control flexibility in operation. As the gas yield properties depend upon operating conditions, interactions of conditions should not be ignored. However, these have able fully capture experimentally. In th...

A two-stage lightweight online dereverberation algorithm for hearing devices is presented in this paper. The approach combines a multi-channel multi-frame linear filter with single-channel single-frame post-filter. Both components rely on power spectral density (PSD) estimates provided by deep neural networks (DNNs). By deriving new metrics analyzing the performance various time ranges, we conf...

Three-dimensional object detection plays a vital role in the field of environment perception autonomous driving, and its results are crucial for subsequent processes. Pillar-based 3D is method to detect objects by dividing point cloud data into pillars extracting features from each pillar. However, current pillar-based object-detection methods suffer problems such as “under-segmentation” false ...

Machine learning and deep techniques are widely used to assess intrusion detection systems (IDS) capable of rapidly automatically recognizing classifying cyber-attacks on networks hosts. However, when destructive attacks becoming more extensive, challenges develop, needing a comprehensive response. Numerous datasets publicly accessible for further analysis by the cybersecurity research communit...

The traditional geomagnetic matching navigation method is based on the correlation criteria operations between measurement sequences and a map. However, when gradient of field small, there are multiple similar data in database to value, which means correlation-based fails. Based idea pattern recognition, this paper constructs two-stage neural network by cascading probabilistic non-fully connect...