An Application Case Study on Multi-sensor Data fusion System for Intelligent Process Monitoring

AbstractMulti-sensor data fusion is a technology to enable combining information from several sources in order to form a unified picture. Focusing on the indirect method, an attempt was made to build up a multi-sensor data fusion system to monitor the condition of grinding wheels with force signals and the acoustic emission (AE) signals. An artificial immune algorithm based multi-signals processing method was presented in this paper. The intelligent monitoring system is capable of incremental supervised learning of grinding conditions and quickly pattern recognition, and can continually improve the monitoring precision. The application case indicates that the accuracy of condition identification is about 87%, and able to meet the industrial need on the whole

MicroRNAs in Human Pituitary Adenomas

MicroRNAs (miRNAs) are a class of recently identified noncoding RNAs that regulate gene expression at posttranscriptional level. Due to the large number of genes regulated by miRNAs, miRNAs play important roles in many cellular processes. Emerging evidence indicates that miRNAs are dysregulated in pituitary adenomas, a class of intracranial neoplasms which account for 10–15% of diagnosed brain tumors. Deregulated miRNAs and their targets contribute to pituitary adenomas progression and are associated with cell cycle control, apoptosis, invasion, and pharmacological treatment of pituitary adenomas. To provide an overview of miRNAs dysregulation and functions of these miRNAs in pituitary adenoma progression, we summarize the deregulated miRNAs and their targets to shed more light on their potential as therapeutic targets and novel biomarkers

InterFormer: Interactive Local and Global Features Fusion for Automatic Speech Recognition

The local and global features are both essential for automatic speech recognition (ASR). Many recent methods have verified that simply combining local and global features can further promote ASR performance. However, these methods pay less attention to the interaction of local and global features, and their series architectures are rigid to reflect local and global relationships. To address these issues, this paper proposes InterFormer for interactive local and global features fusion to learn a better representation for ASR. Specifically, we combine the convolution block with the transformer block in a parallel design. Besides, we propose a bidirectional feature interaction module (BFIM) and a selective fusion module (SFM) to implement the interaction and fusion of local and global features, respectively. Extensive experiments on public ASR datasets demonstrate the effectiveness of our proposed InterFormer and its superior performance over the other Transformer and Conformer models.Comment: Accepted by Interspeech 202

Simulation study of Ferricyanide/Ferrocyanide concentric annulus thermocell with different electrode spacing and cell direction

Thermogalvanic cell also named as thermocell is a new type of technology converting low-grade thermal energy to electricity. In this study, we establish an one-dimensional model of a Fe(CN)63-/4- concentric annulus thermocell and evaluate the influence of electrode spacing and cell direction on the cell performance. Results indicate the ratio of electrolyte thermal resistance to total thermal resistance plays a crucial role in cell performance while electric resistance has relatively less influence. The power of thermocell rises significantly as the electrode spacing increases, from about 0.75mW in both directions to 1.75 mW in horizontal direction and 2.75 mW in vertical direction. Convection of electrolyte is unfavorable to cell performance and the critical electrode spacing where convection begins to affect heat transfer is predicted to be the optimized spacing. At all values of electrode spacing in this study, thermocell in vertical direction performs better than that of horizontal direction