Code2vect: An efficient heterogenous data classifier and nonlinear regression technique

The aim of this paper is to present a new classification and regression algorithm based on Artificial Intelligence. The main feature of this algorithm, which will be called Code2Vect, is the nature of the data to treat: qualitative or quantitative and continuous or discrete. Contrary to other artificial intelligence techniques based on the “Big-Data,” this new approach will enable working with a reduced amount of data, within the so-called “Smart Data” paradigm. Moreover, the main purpose of this algorithm is to enable the representation of high-dimensional data and more specifically grouping and visualizing this data according to a given target. For that purpose, the data will be projected into a vectorial space equipped with an appropriate metric, able to group data according to their affinity (with respect to a given output of interest). Furthermore, another application of this algorithm lies on its prediction capability. As it occurs with most common data-mining techniques such as regression trees, by giving an input the output will be inferred, in this case considering the nature of the data formerly described. In order to illustrate its potentialities, two different applications will be addressed, one concerning the representation of high-dimensional and categorical data and another featuring the prediction capabilities of the algorithm.     

云制造平台加工能力分享调度优化研究

云制造平台加工能力分享的调度优化是云制造模式的核心运营问题。为提高云制造平台对参与能力分享企业资源的利用率,解决实际云制造需求环境下企业级制造资源调度问题,达到云制造平台动态实时的要求,以最小化工期和成本为目标函数,构建了基于平台并面向分享的云加工能力调度模型。为快速求解多个云任务订单的最优调度序列,引入任务简易编码和随机权重,设计了改进的二阶粒子群算法,并提出可分享加工能力时间窗的更新策略。最后,通过算例验证云制造平台加工能力调度机制的可行性和有效性。     

A new class of conformable spectral observers for signal reconstruction

In this work, the design of spectral observers for signal reconstruction based on Kalman filters is performed and evaluated. The conformable derivative and the beta‐derivative were used to design the Kalman filters. Both derivatives satisfy the same formulas of the classical derivation, eg, the chain rule. The derivative order, the Ricatti equation parameters, and the observers tuning parameters were optimized using an optimization algorithm based on the bat's echolocation behavior (Bat algorithm). The simulation results showed the advantages of using the proposed observers for the signal reconstruction.     

Visual Speech Recognition with Lightweight Psychologically Motivated Gabor Features

Extraction of relevant lip features is of continuing interest in the visual speech domain. Using end-to-end feature extraction can produce good results, but at the cost of the results being difficult for humans to comprehend and relate to. We present a new, lightweight feature extraction approach, motivated by human-centric glimpse-based psychological research into facial barcodes, and demonstrate that these simple, easy to extract 3D geometric features (produced using Gabor-based image patches), can successfully be used for speech recognition with LSTM-based machine learning. This approach can successfully extract low dimensionality lip parameters with a minimum of processing. One key difference between using these Gabor-based features and using other features such as traditional DCT, or the current fashion for CNN features is that these are human-centric features that can be visualised and analysed by humans. This means that it is easier to explain and visualise the results. They can also be used for reliable speech recognition, as demonstrated using the Grid corpus. Results for overlapping speakers using our lightweight system gave a recognition rate of over 82%, which compares well to less explainable features in the literature.     

Full physicochemical characterization of malic acid: Emphasis in the potential as food ingredient and application in pectin gels

Malic acid, a carboxylic acid most found in fruits, is a smooth taste substance used as flavoring and preservative agent in foods, although not as used as citric acid. There are no studies focusing in quantitative results or investigations on its physicochemical properties, useful to the food industry, or even the confirmation of its calcium chelating, buffer texturizer and antioxidant alleged properties. Thus, the aim of this work was the assessment of most physicochemical properties of malic acid, solid and in solution, that could be useful to the food industry understand its real potential. The following analyses were carried out: melting point; structure (NMR, XRD, FTIR and SEM/EDS); TGA/DTG; solubility, hygroscopicity; antioxidant activity, iron chelating and antibacterial activities and stability of pectin gels. The melting temperature found was 129.71 °C. TGA/DTG exhibited first loss of mass around 140 °C. In the temperature range of 10 to 55 °C, it exhibited a high solubility in water, from 48.12 to 61.49 (100w), respectively. The tested bacteria, related to food spoilage, were inhibited by DL-malic acid 10% or higher. Chelating and antioxidant activities showed expressive results even in 1% solution. Pectin gels with malic acid had stronger structure and less syneresis than citric acid gels. In addition, calcium chelating, buffer texturizer and antioxidant properties were confirmed. Thus, malic acid has potential to be applied in a wide variety of food products as fortified beverages, frozen and refrigerated items, oils, pectin gels, hard and soft candies, and biofilms, due to all the characteristics quantified.     

医学影像处理的深度学习可解释性研究进展

随着医学影像数据的迅速增长，传统的影像分析方法给医生带来巨大挑战。利用计算机视觉技术提供自动或半自动辅助诊断，可大大缓解人工阅片压力，提高诊断的准确性，促进医疗流程的标准化建设等。目前，深度学习卷积神经网络在医学影像处理中已取得不俗表现，但深度学习“黑匣子”的不可解释性阻碍了智能医疗诊断的发展。为增强对医学影像数据处理的深度学习可解释性的了解，对近几年相关研究进展进行了综述。首先，综述了深度学习在医学领域的应用现状及面临的问题，对神经网络的可解释性内涵进行了讨论；然后，从现有深度学习可解释性的常见方法出发，重点讨论了医学影像处理的深度学习可解释性研究进展；最后，探讨了医学影像处理的深度学习可解释性的发展趋势。     

Measuring technical and environmental efficiency in a state-contingent technology

Most developed countries support farming activities through policies that are tailored to meet their specific social, economic and environmental objectives. Economic and environmental efficiency have recently become relevant targets of most of these policies, whose sound implementation can be enhanced by monitoring farm performance from a multidimensional perspective. This paper proposes farm-level technical and environmental efficiency measures that recognize the stochastic conditions in which production takes place. A state-contingent framework is used to model production uncertainty. An implementable representation of the technology is developed using data envelopment analysis. The application focuses on a sample of Catalan arable crop farms. Results suggest that technical efficiency is slightly lower in bad than in good growing conditions. Nitrogen pollution can decrease substantially more under good than bad growing conditions.     

不断向自然与金属冶金学习的高分子加工

总结了高分子材料加工的发展趋势及发展历程,并指出过去很多加工新技术的出现都得益于从自然现象及其他材料行业中获得很好的借鉴,如从蜘蛛吐丝发展出溶液纺丝成型、从玻璃吹制发展出吹塑成型、从金属锻造发展出压延成型及固相拉拔成型等;随后针对生物基可生物降解的立构复合型聚乳酸难以采用传统熔融加工方法成型的问题,借鉴金属粉末冶金加工的思路,提出了一种通过低温烧结制备高性能立构复合型聚乳酸制品的新方法.通过这种加工方法不仅可以有效解决立构复合型聚乳酸在熔融加工过程中熔体稳定性差、易降解的问题,而且可以制得耐热性好、光学透明度高、耐水解降解性佳、综合力学性能优异的高性能聚乳酸制品.     

Silver‐Assisted Chemical Etching on Silicon with Polyvinylpyrrolidone‐Mediated Formation of Silver Dendrites

Metal‐assisted chemical etching (MaCE) on silicon (Si)—mediated by polyvinylpyrrolidone (PVP)—is systematically investigated herein. It is found that the morphologies and crystallographic natures of the grown silver (Ag) dendrites can be significantly modulated, with the presence of PVP in the MaCE process leading to the formation of faceted Ag dendrites preferentially along the (111) crystallographic phase, rather than along the (200) phase. Further explorations of the PVP‐mediated effect on Si etching are also revealed. In contrast to the aligned Si nanowires formed by MaCE without PVP addition, only distributed nanopores with sizes of 200 to 400 nm appear on the Si surfaces in the presence of PVP. The origin of surface polishing on Si in the PVP‐mediated MaCE process can be attributed to the distinct transport pathway of holes supplied by the Ag⁺ ions, where the holes are injected directly into the primary Ag seeds, rather than through Ag dendrites, thus leading to the isotropic etching of the Si surface.