Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Semantic word shifts in a scientific domain

Understanding semantic word shifts in scientific domains is essential for facilitating interdisciplinary communication. Using a data set of published papers in the field of information retrieval (IR), this paper studies the semantic shifts of words in IR based on mining per-word topic distribution over time. We propose that semantic word shifts not only occur over time, but also over topics. The shifts are examined from two perspectives, the topic-level and the context-level. According to the over-time word-topic distribution, stable words and unstable words are recognized. The diverging and converging trends in the unstable type reveal characteristics of the topic evolution process. The context-level shifts are further detected by similarities between word vectors. Our work associates semantic word shifts with the evolving of topics, which facilitates a better understanding of semantic word shifts from both topics and contexts.     

Do funded papers attract more usage?

Research funding has been seen as one of the most important resource in the reward system of science. And usage of publications denotes an interesting perspective of user behavior in scientific communication. This study aims to address the relationship between funding and Usage Count, which is a new metrics item established on the platform of Web of Science. Full records of 300,010 articles published in 2013 were downloaded in October 2015, and divided into six disciplines, including information science library science, education educational research, economics, computer science, materials science, and chemistry. Seven indicators were proposed to measure the impact, including Funding rate, Citation per paper, Usage rate, Usage per paper, Citation difference, Usage difference, and Conversion rate. It concluded funding has impact on usage and citation, and funded papers attract more usage, but varying in different disciplines. Usage Count can be used in the extension of citation metrics but with limits. This study originally engages with usage metrics and detected that there is positive correlation between usage and funding.     

Adaptive Finite-time Tracking Control for Class of Uncertain Nonlinearly Parameterized Systems with Input Delay

International Journal of Control, Automation and Systems - In this paper, the tracking problem for a class of uncertain nonlinearly parameterized systems with input delay based the adaptive...     

A multi-criteria context-sensitive approach for social image collection summarization

Recent increase in the number of digital photos in the content sharing and social networking websites has created an endless demand for techniques to analyze, navigate, and summarize these images. In this paper, we focus on image collection summarization. Earlier methods in image collection summarization consider representativeness and diversity criteria while recent ones also consider other criteria such as image quality, aesthetic or appeal. In this paper, we propose a multi-criteria context-sensitive approach for social image collection summarization. In the proposed method, two different sets of features are combined while each one looks at different criteria for image collection summarization: social attractiveness features and semantic features. The first feature set considers different aspects that make an image appealing such as image quality, aesthetic, and emotion to create attractiveness score for input images while the second one covers semantic content of images and assigns semantic score to them. We use social network infrastructure to identify attractiveness features and domain ontology for extracting ontology features. The final summarization is provided by integrating the attractiveness and semantic features of input images. The experimental results on a collection of human generated summaries on a set of Flickr images demonstrate the effectiveness of the proposed image collection summarization approach.     

采煤机行走轮参数化分析软件设计

针对电牵引采煤机渐开线行走轮在ANSYS分析中存在的问题,提出运用APDL语言命令直接建模,并通过VB与ANSYS的交互运行途径,设计了基于VB界面和程序的软件,实现了利用VB界面直接输入参数并调用ANSYS对行走轮自动建模、加载和计算的有限元分析。验证结果表明,该软件减少了设计人员的重复劳动,提高了行走轮的设计效率和水平,具有一定的工程实用价值。     

大洋勘探船压载水系统设计

分析和研究最新生效的几种常用压载水管理公约规范,调研和对比目前市场上常用的几种压载水处理措施,综合对比分析各种压载水处理技术并结合大洋勘探船的特点选择合适的压载水处理技术,设计研究一型经济和环保的压载水系统,并进行压载水处理装置设备选型、系统设计和相关设备布置等。     

Efficient PL Emission from p-type Porous Silicon: A Comparative Study for Selection of Effective Anodization Parameters

The physical mechanism of highly efficient photoluminescence (PL) emission from p-type silicon is described by a comparative study of the effectiveness of the etching parameters in an electrochemical anodization technique. Two series of porous silicon samples were prepared in a combination of anodization current and time, to maintain the total amount of anodic charge transfer constant. Photoluminescence studies show that irrespective of the amount of charge transfer, the samples prepared with comparatively higher current density show an efficient PL as well as stronger blueshift in the emission energy vis-à-vis the samples prepared for longer durations. An overall decrease in crystallite size, as estimated by Raman spectral analysis, was observed for both series of samples with the progress of charge transfer. Comparative analysis shows a marginal difference in crystallite size for both series of samples in the initial state of charge transfer, whereas major differences arise at higher values. This is explained with the formation of silicon suboxide on the porous surface at higher current density, leading to initiation of side wall reaction, and higher reduction rate in crystallite size as well as strong luminescence due to the carrier quantum confinement effect.     

A quarter century of wine pigment discovery

The red grape berry pigments, anthocyanins, were characterized in the early 20th century, but investigations of wine pigments were stymied during that era. The question of their identity was a major challenge for wine chemists. A number of techniques showed that the pigments were polymeric in nature. Some structures were postulated by mid-century based on reactions between anthocyanins and condensed tannin, and later postulated wine pigments were observed in model reactions. Some related compounds were then observed in wine. By the end of the 20th century, the ionization of non-volatiles for mass spectrometry opened the door to these compounds. In addition, a new class of compounds was observed, the pyranoanthocyanins, a product of fermentation and aging metabolites with anthocyanins. These compounds possess the pigment stability to SO₂ and pH change that is characteristic of aged red wine. Aging experiments show a dynamic situation with shifts in the population of pigment classes over time. The very large number of diverse pigments explains why it has been so difficult to answer the century-old question of the structure of wine pigments. Our current understanding is founded on the use of mass spectral analysis using electrospray and related ionization techniques over the last 25 years. Future progress will rely on more sophisticated analysis of this very complex mixture of substances. © 2019 Society of Chemical Industry