CUCL: Codebook for Unsupervised Continual Learning

The focus of this study is on Unsupervised Continual Learning (UCL), as it presents an alternative to Supervised Continual Learning which needs high-quality manual labeled data. The experiments under the UCL paradigm indicate a phenomenon where the results on the first few tasks are suboptimal. This phenomenon can render the model inappropriate for practical applications. To address this issue, after analyzing the phenomenon and identifying the lack of diversity as a vital factor, we propose a method named Codebook for Unsupervised Continual Learning (CUCL) which promotes the model to learn discriminative features to complete the class boundary. Specifically, we first introduce a Product Quantization to inject diversity into the representation and apply a cross quantized contrastive loss between the original representation and the quantized one to capture discriminative information. Then, based on the quantizer, we propose an effective Codebook Rehearsal to address catastrophic forgetting. This study involves conducting extensive experiments on CIFAR100, TinyImageNet, and MiniImageNet benchmark datasets. Our method significantly boosts the performances of supervised and unsupervised methods. For instance, on TinyImageNet, our method led to a relative improvement of 12.76% and 7% when compared with Simsiam and BYOL, respectively.Comment: MM '23: Proceedings of the 31st ACM International Conference on Multimedi

Outlook on ecologically improved composites for aviation interior and secondary structures

Today, mainly man-made materials such as carbon and glass fibres are used to produce composite parts in aviation. Renewable materials such as natural fibres or bio-sourced resin systems have not found their way into aviation, yet. The project ECO-COMPASS aims to evaluate the potential applications of ecologically improved composite materials in the aviation sector in an international collaboration of Chinese and European partners. Natural fibres such as flax and ramie will be used for different types of reinforcements and sandwich cores. Furthermore, the bio-based epoxy resins to substitute bisphenol-A based epoxy resins in secondary structures are under investigation. Adapted material protection technologies to reduce environmental influence and to improve fire resistance are needed to fulfil the demanding safety requirements in aviation. Modelling and simulation of chosen eco-composites aims for an optimized use of materials while a life cycle assessment aims to prove the ecological advantages compared to synthetic state-of-the-art materials. In this paper, the status of selected ecologically improved materials will be presented with an outlook for potential application in interior and secondary structures

The effect of intumescent mat on post-fire performance of carbon fibre reinforced composites

This study investigated the effect of intumescent mats (M1 and M2) with different compositions on the post-fire performance of carbon fibre reinforced composites. The sandwich structure was designed for composites where M1 (carbon fibre reinforced composite-M1) or M2 (carbon fibre reinforced composite-M2) mats were covered on the composite surface. A significant reduction in the peak heat release rate and total heat release was observed from the cone calorimetric data, and carbon fibre reinforced composite-M1 showed the lowest value of 148 kW/m2 and 29 MJ/m2 for peak heat release rate and total heat release, respectively. In addition, a minor influence on mechanical properties was observed due to the variation of composite thickness and resin volume in the composite. The post-fire properties of composite were characterised, and the M1 mat presented better retention of flexural strength and modulus. The feasibility of two-layer model was confirmed to predict the post-fire performance of composites and reduce the reliance on the large amounts of empirical data. © The Author(s) 2019

REPORTAJE CARMELO ARTILES BOLAÑOS. INFECAR [Material gráfico]

Copia digital. Madrid : Ministerio de Educación, Cultura y Deporte, 201

A Novel Hybrid of a Fading Filter and an Extreme Learning Machine for GPS/INS during GPS Outages

In this paper, a novel algorithm based on the combination of a fading filter (FF) and an extreme learning machine (ELM) is presented for Global Positioning System/Inertial Navigation System (GPS/INS) integrated navigation systems. In order to increase the filtering accuracy of the model, a variable fading factor fading filter based on the fading factor is proposed. It adjusts the fading factor by the ratio of the estimated covariance before and after the moment which proves to have excellent performance in our experiment. An extreme learning machine based on a Fourier orthogonal basis function is introduced that considers the deterioration of the accuracy of the navigation system during GPS outages and has a higher positioning accuracy and faster learning speed than the typical neural network learning algorithm. In the end, a simulation and real road test are performed to verify the effectiveness of this algorithm. The results show that the accuracy of the fading filter based on a variable fading factor is clearly improved, and the proposed improved ELM algorithm can provide position corrections during GPS outages more effectively than the other algorithms (ELM and the traditional radial basis function neural network)

A Novel Method to Estimate the Sea State for Recycling Work on the Sea Surface

The recycling of marine exploration equipment after it has surfaced is greatly affected by sea state. In order to estimate the sea state in real time, this paper proposes a method for measuring wave elevation, which modifies the integrated results of GNSS/SINS in the up direction by virtual horizontal lines to extract wave fluctuation information. From these wave information, the significant wave heights (SWH) can be calculated as the only input parameter of P-M spectrum, and a series of wave height data can be further simulated. When the GNSS is interrupted due to severe sea state, the simulated data can be integrated with the SINS to deal with the data distortion problem. The simulation results show that the application of wave spectrum in the GNSS intermittent situation has obvious improvement effect and important significance

Effects of Shugan Hewei Granule on Depressive Behavior and Protein Expression Related to Visceral Sensitivity in a Rat Model of Nonerosive Reflux Disease

Objective. To explore the effect of Shugan Hewei Granule (SGHWG) and to provide the experimental basis for its clinical application. Methods. 40 healthy male Wistar rats were divided into 5 groups, with 8 rats in each group, including control group, model group, normal saline (NS) group, SGHWG group, and Rabeprazole group. The control group was not treated. The model group was treated with fructose intake and mental stress to be the model of NERD. The other groups were treated as the model group and then gavaged with the corresponding drugs. The pH value of lower third of esophagus, immobile time in tail suspension test, CRF protein expression in both hypothalamus and anterior cingulate cortex (ACC), and SP protein in esophageal mucosa in lower third of esophagus detected by immunofluorescence and NMDAR1 protein expression in spinal cord detected by immunohistochemistry of each group were compared. Results. The pH values of both the SGHWG group and the Rabeprazole group were higher than that of the model group (P<0.01), but the Rabeprazole group increased more obviously. The immobile time of the SGHWG group was shorter than that of the model group (P<0.01) and the Rabeprazole group (P<0.05). The expression of the CRF in the hypothalamus and ACC, NMDAR1 in the spinal cord, and SP in the esophageal mucosa in lower third of esophagus of the SGHWG group decreased significantly, compared with the model group (P<0.01), and was obviously lower than that in the Rabeprazole group (P<0.05). Conclusions. This study provided an evidence that SGHW formula was inferior to Rabeprazole in acid inhibition, but it might reduce the expression of CRF protein of hypothalamus and ACC, lower the levels of NMDAR1 in spinal dorsal horn and SP in esophageal mucosa in lower third of esophagus, and regulate depressive behavior simultaneously, related to the improvement of visceral hypersensitivity in rat model of NERD

Development of SFM of probing sensor look-alike

This paper mainly introduces the development of a cantilever driving scanner. Based on this scanner a up-scanning mode of SFM has been developed which was originally aiming at mounting on the top of NMM as a probing sensor. SFM was connected to electronic control unit of CSPM a nano-instrument of CBeing to do experiment and test. As a result, it successfully scanned and imaged the sample within 23μm×23μm×5μm scanning range. Tests, analysis and calculations shows that its lateral and vertical resolutions are 0.25nm and 0.1nn respectively on all axes for all scan sizes, and lateral accuracy is 5% on lateral axes for all scan sizes without any software and hardware correction and compensation