Model-Based Design Space Exploration for FPGA-based Image Processing Applications Employing Parameterizable Approximations

The increasing demand for low power consumption and high computational performance is outpacing available technological improvements in embedded systems. Approximate computing is a novel design paradigm trying to bridge this gap by leveraging the inherent error resilience of certain applications and trading in quality to achieve reductions in resource usage. Numerous approximation methods have emerged in this research field. While these methods are commonly demonstrated in isolation, their combination can increase the achieved benefits in complex systems. However, the propagation of errors throughout the system necessitates a global optimization of parameters, leading to an exponentially growing design space. Additionally, the parameterization of approximated components must consider potential cross-dependencies between them. This work proposes a systematic approach to integrate and optimally configure parameterizable approximate components in FPGA-based applications, focusing on low-level but high-bandwidth image processing pipelines. The design space is explored by a multi-objective genetic algorithm which takes parameter dependencies between different components into account. During the exploration, appropriate models are used to estimate the quality-resource trade-off for probed solutions without the need for time-consuming synthesis. We demonstrate and evaluate the effectiveness of our approach on two image processing applications that employ multiple approximations. The experimental results show that the proposed methods are able to produce a wide range of Pareto-optimal solutions, offering various choices regarding the desired quality-resource trade-off.     

Investigation the correlation between chemical structure and swelling,thermal and flocculation properties of carboxymethylcellulose hydrogels

Hydrophilic polymer networks (hydrogels) based on sodium carboxymethylcellulose (NaCMC) and polycarboxylic acids (oxalic, succinic, citric and adipic) as cross-linking agents are synthesized by esterification reaction; one series of NaCMC hydrogels cross-linked with citric acid is prepared with acrylamide and acrylic acid (Aam/Aac) copolymers using the design of semi-interpenetrating polymer networks (semi-IPN), in order to increase their potential application for flocculation purposes. The Infrared spectroscopy (FTIR) of hydrogels confirms the esterification reaction between NaCMC and cross-linking agents. Results of swelling measurements show that citric acid in the amount of 15 wt% gives the hydrogels with the best absorption capacity. The results of Differential scanning calorimetry (DSC) and Thermal gravimetric analysis (TGA) show no significant difference in thermal properties of neat and semi-interpenetrating NaCMC hydrogels. The amorphous nature of hydrogels is confirmed by X-ray diffraction analysis (XRD). The results of flocculation study show that combination of NaCMC network and Aam/Aac copolymer with initial mass ratio of 10/90 creates a theoretical platform for the production of flocculant which could show high efficacy in purifying of water dominated by positively charged particles.     

Ultra-Robust Flexible Electronics by Laser-Driven Polymer-Nanomaterials Integration

Polyethylene terephthalate (PET) is the most widely used polymer in the world. For the first time, the laser-driven integration of aluminum nanoparticles (Al NPs) into PET to realize a laser-induced graphene/Al NPs/polymer composite, which demonstrates excellent toughness and high electrical conductivity with the formation of aluminum carbide into the polymer is shown. The conductive structures show an impressive mechanical resistance against >10000 bending cycles, projectile impact, hammering, abrasion, and structural and chemical stability when in contact with different solvents (ethanol, water, and aqueous electrolytes). Devices including thermal heaters, carbon electrodes for energy storage, electrochemical and bending sensors show this technology's practical application for ultra-robust polymer electronics. This laser-based technology can be extended to integrating other nanomaterials and create hybrid graphene-based structures with excellent properties in a wide range of flexible electronics’ applications.     

Conversion kinetics of container glass batch melting

Understanding the batch-to-glass conversion process is fundamental to optimizing the performance of glass-melting furnaces and ensuring that furnace modeling can correctly predict the observed outcome when batch materials or furnace conditions change. To investigate the kinetics of silica dissolution, gas evolution, and primary foam formation and collapse, we performed X-ray diffraction, thermal gravimetry, feed expansion tests, and evolved gas analysis of batch samples heated at several constant heating rates. We found that gas evolving reactions, foaming, and silica dissolution depend on the thermal history of the batch in a similar manner: the kinetic parameters of each process were linear functions of the square root of the heating rate. This kinetic similarity reflects the stronger-than-expected interdependence of these processes. On the basis of our results, we suggest that changes in furnace operating conditions, such as firing or boosting, influence the melting rate less than what one would expect without consideration of batch conversion kinetics.     

Sub-band coding of hexagonal images

According to the circle-packing theorem, the packing efficiency of a hexagonal lattice is higher than an equivalent square tessellation. Consequently, in several contexts, hexagonally sampled images compared to their Cartesian counterparts are better at preserving information content. In this paper, novel mapping techniques alongside the wavelet compression scheme are presented for hexagonal images. Specifically, we introduce two tree-based coding schemes, referred to as SBHex (spirally-mapped branch-coding for hexagonal images) and BBHex (breadth-first block-coding for hexagonal images). Both of these coding schemes respect the geometry of the hexagonal lattice and yield better compression results. Our empirical results show that the proposed algorithms for hexagonal images produce better reconstruction quality at low bits per pixel representations compared to the tree-based coding counterparts for the Cartesian grid.     

An enhancement algorithm based on adaptive updating template with Gaussian model for Si3N4 ceramic bearing roller surface defects detection

The method based on machine vision image processing is used to detect the surface defects of Si₃N₄ bearing roller. Owing to the variety of defects, small area and low contrast, it is easy to miss or error detection. In this paper, an adaptive update template defect enhancement algorithm based on Gaussian model is proposed. First, a large number of surface images of Si₃N₄ bearing roller are collected to obtain the non-defect background statistical feature, and the background characteristic curve is fitted by Gaussian model. Further, the initial background template is gained according to the Gaussian curve. Then, combined with the gray distribute of defect images and initial background template, unique adaptive update template can be established. Finally, subtraction operation and nonlinear enhancement are used to improve the comparison of defect information and background. Through inverse sorting, adaptive threshold segmentation and Canny operation, the precise positioning of defects is realized. The enhancement algorithm can effectively enhance the contrast and eliminate the influence of noise. The average detection time is 0.84s, and the detection accuracy is 96.2%.     

The effects of fuel variability on the electrical performance and durability of a solid oxide fuel cell operating on biohythane

Biohythane is typically composed of 60/30/10 vol% CH₄/CO₂/H₂ and can be produced via two-stage anaerobic digestion of renewable and low carbon biomass with much greater efficiency compared with CH₄/CO₂ biogas. This work investigates the effects of fuel variability on the electrical performance and fuel processing of a commercially available anode supported solid oxide fuel cell (SOFC) operating on biohythane mixtures at 750 °C. Cell electrical performance was characterised using current-voltage curves and electrochemical impedance spectroscopy. Fuel processing was characterised using quadrupole mass spectroscopy. It is shown that when H₂/CO₂ is blended with CH₄ to make biohythane, the SOFC efficiency is significantly increased, high SOFC durability is achieved, and there are considerable savings in CH₄ consumption. Enhanced electrical performance was due to the additional presence of H₂ and promotion of CH₄ dry reforming, the reverse Boudouard and reverse water-gas shift reactions. These processes alleviated carbon deposition and promoted electrochemical oxidation of H₂ as the primary power production pathway. Substituting 50 vol% CH₄ with 25/75 vol% H₂/CO₂ was shown to increase cell power output by 81.6% at 0.8 V compared with pure CH₄. This corresponded to a 3.4-fold increase in the overall energy conversion efficiency and a 72% decrease in CH₄ consumption. A 260 h durability test demonstrated very high cell durability when operating on a typical 60/30/10 vol% CH₄/CO₂/H₂ biohythane mixture under high fuel utilisation due to inhibition of carbon deposition. Overall, this work suggests that decarbonising gas grids by substituting natural gas with renewably produced H₂/CO₂ mixtures (rather than pure H₂ derived from fossil fuels), and utilising in SOFC technology, gives considerable gains in energy conversion efficiency and carbon emissions savings.     

泥鳅多糖的研究进展

近年来随着泥鳅养殖及产业化的快速发展, 泥鳅资源的开发和高值化利用已成为研究热点。泥鳅是一种含有丰富优质蛋白、脂肪酸以及微量元素的营养健康食品, 具备多种保健功能和药用价值, 其中泥鳅多糖是从泥鳅中提取得到的一种游离中性多糖, 具有耐缺氧、抗肿瘤、抗氧化、调节免疫、降血糖、抗炎等功能。本文主要综述了泥鳅多糖的制备方法、分离提纯方法、结构表征、生物活性、精深加工等方面的研究进展,旨在为泥鳅多糖的高值化利用提供一些理论基础, 为泥鳅产业链的快速发展提供新的发展方向。