Quadratic polynomial guided fuzzy C-means and dual attention mechanism for medical image segmentation

Medical image segmentation is the most complex and important task in the field of medical image processing and analysis, as it is linked to disease diagnosis accuracy. However, due to the medical image's high complexity and noise, segmentation performance is limited. We propose a novel quadratic polynomial guided fuzzy C-means and dual attention mechanism composite network model architecture to address the aforementioned issues (QPFC-DA). It has mechanisms for channel and spatial edge attention, which guide the content and edge segmentation branches, respectively. The bi-directional long short-term memory network was added after the two content segmentation branches to better integrate multi-scale features and prevent the loss of important features. Furthermore, the fuzzy C-means algorithm guided by the quadratic polynomial can better distinguish the image's weak edge regions and has a degree of noise resistance, resulting in a membership matrix with less ambiguity and a more reliable segmentation result. We also conducted comparison and ablation experiments on three medical data sets. The experimental results show that this method is superior to several other well-known methods.     

CoGCN: Combining co‐attention with graph convolutional network for entity linking with knowledge graphs

Entity linking is a fundamental task in natural language processing. The task of entity linking with knowledge graphs aims at linking mentions in text to their correct entities in a knowledge graph like DBpedia or YAGO2. Most of existing methods rely on hand‐designed features to model the contexts of mentions and entities, which are sparse and hard to calibrate. In this paper, we present a neural model that first combines co‐attention mechanism with graph convolutional network for entity linking with knowledge graphs, which extracts features of mentions and entities from their contexts automatically. Specifically, given the context of a mention and one of its candidate entities' context, we introduce the co‐attention mechanism to learn the relatedness between the mention context and the candidate entity context, and build the mention representation in consideration of such relatedness. Moreover, we propose a context‐aware graph convolutional network for entity representation, which takes both the graph structure of the candidate entity and its relatedness with the mention context into consideration. Experimental results show that our model consistently outperforms the baseline methods on five widely used datasets.     

Safe and intuitive manual guidance of a robot manipulator using adaptive admittance control towards robot agility

Key areas of robot agility include methods that increase capability and flexibility of industrial robots and facilitate robot re-tasking. Manual guidance can achieve robot agility effectively, provided that a safe and smooth interaction is guaranteed when the user exerts an external force on the end effector. We approach this by designing an adaptive admittance law that can adjust its parameters to modify the robot compliance in critical areas of the workspace, such as near and on configuration singularities, joint limits, and workspace limits, for a smooth and safe operation. Experimental validation was done with two tests: a constraint activation test and a 3D shape tracing task. In the first one, we validate the proper response to constraints and in the second one, we compare the proposed approach with different admittance parameter tuning strategies using a drawing task where the user is asked to guide the robot to trace a 3D profile with an accuracy or speed directive and evaluate performance considering path length error and execution time as metrics, and a questionnaire for user perception. Results show that appropriate response to individual and simultaneous activation of the aforementioned constraints for a safe and intuitive manual guidance interaction is achieved and that the proposed parameter tuning strategy has better performance in terms of accuracy, execution time, and subjective evaluation of users.     

矿用救生舱环境监控系统软件的研究

给出了矿用救生舱环境监控系统的组成,主要介绍了该系统软件的功能设计、总体架构及界面设计方案。该系统软件可实时显示各传感器的运行状态和检测数据、舱内气体余量、电源电量、照明灯状态、空气净化状态、自动控制状态、舱门状态等,人机交互界面友好,操作简便。该软件经长期连续运行实验,工作正常,达到了设计要求。     

IPv6在QoS上的三项重要改进

本文主要分析了IPv6相对于IPv4在QoS上所做的基本报头、ICMP控制机制及基本报头中的QoS元素三项改进,从而为有效支持QoS提供理论支持。     

基于光通信的数据单向导入系统的设计与实现

随着信息网络的日趋成熟,网络信息安全尤其是内网信息安全,越来越受到人们的关注,成为一时研究的热点。其中如何防止在移动存储设备与内网计算机信息交流过程中内网信息流失的问题,显得尤为迫切。为此,本文提出一种基于光通信的数据单向导入系统,为用户提供一种安全地将信息或者数据单向导入到内网的解决方案。利用光的单向性,从传输通道上卡断了反向的可能,有效地保护内网的机密信息不会流失到外部,同时做到良好的人机交互,用户可以任意选择存储设备中的文件发送。     

碳质金矿中碳质物及其“劫金”机理研究进展

碳质金矿是重要的难处理金矿资源之一,碳质物“劫金”是金浸出率低下的主要原因。碳质物组分复杂,不同组分的碳质物的“劫金”能力和“劫金”行为存在差异,磨矿和浸出环节对碳质物的“劫金”能力也会产生影响,这些因素均能直接影响金的浸出率。通过系统总结碳质金矿中碳质物在组成特征、“劫金”机理及“劫金”能力的影响因素等方面的研究进展,对碳质物“劫金”机理现有研究工作的不足及未来研究方向进行了探讨,为碳质金矿碳质物劫金机理及预处理工艺的研究提供了重要参考。     

Determination of the solubility parameter of poly(ethylene oxide) at 25°C by gas-liquid chromatography

The solubility parameter of poly(ethylene oxide) at 25°C has been determined using the method developed by DiPaola-Baranyi and Guillet, by the extrapolation of the values of the interaction parameter χ, at high temperatures, ranging from 70°–90°, 90°–110° and 110°–130°C down to 25°C. The values of the solubility parameter obtained, depending on the temperature ranges employed, are 9.8, 9.9 and 10.1, respectively.     

Selective solvation of polystyrene in tetralin/cyclohexane mixtures

Refractive index increments and density increments have been measured at 307.6K for polystyrene in binary solvents of 1,2,3,4-tetrahydronaphthalene (tetralin, TET) and cyclohexane over the whole range of solvent composition. Comparison of these increments with the corresponding values obtained at dialysis equilibrium (i.e. at constant chemical potential of low molecular weight species) yielded the coefficients of selective adsorption (γ₁) of TET by the polymer. Positive values of γ₁ were exhibited at solvent compositions up to 78% (v/v) of the thermodynamically better solvent, TET. Theoretical curves of γ₁ vs. composition were calculated on the basis of, firstly, relevant interaction parameters and, secondly, interaction parameters in conjunction with solubility parameters. Both procedures afforded self-consistent results, which were, however, uniformly lower than the experimental values of γ₁.     

Guayule seedling response to nitrogen fertilizers

Slow growth and high seedling mortality limit direct seeding establishment of guayule (Parthenium argentatum G.). This study was conducted to assess seedling growth enhancement by the addition of different rates and forms of N fertilizers and Ca salts. Experiments were conducted in a greenhouse with cultivar 593 under both surface and subirrigated conditions using water low in salts (salinity of 0.8 dSm^–1, SAR of 5.0 and 10 mg Ca L^–1). Under surface-irrigated conditions, seedling height and fresh plant weight increased with N application to the irrigation water to 70 mg L^–1. The best seedling growth was observed when (NH₄)₂SO₄ was added in combination with CaCl₂ or CaSO₄. Progressively less growth was observed by addition of (NH₄)₂SO₄ alone, CO(NH₂)₂ plus CaSO₄, CO(NH₂)₂ alone and Ca(NO₃)₂. When seedlings were subirrigated, however, the best growth was observed with Ca(NO₃)₂. Intermediate growth was obtained with (NH₄)₂SO₄ plus CaSO₄ and lowest growth rates with (NH₄)₂SO₄ alone. These differential responses may be explained by the differences in leaching and volatile characteristics of the N forms. Growth enhancement from N and Ca additions increased with time with significant increases 45 days after seeding. Nitrogen application with Ca may be effective amendment in promoting subsequent growth of direct seeded guayule.