Numerical integration for the inverse dynamics of a large class of cranes

Multibody System Dynamics - A recently developed index reduction method is applied to comparatively complicated underactuated mechanical systems in the context of inverse dynamics. The inverse...     

An image segmentation method based on Mumford–Shah model with mask factor and neighborhood factor

Pattern Analysis and Applications - A novel image segmentation model is proposed to improve the stability of existing segmentation methods. In the proposed model, we introduce two factors into the...     

A Two-Dimensional Numerical Analysis for Thermal Performance of an Intermittently Operated Radiant Floor Heating System in a Transient External Climatic Condition

Abstract

Building thermal inertia and operation control strategies have impacted on the thermal performance of a radiant floor heating system. This study conducts a two-dimensional numerical analysis of an intermittently operated radiant floor heating system using the Re-Normalization Group model with Discrete Ordinates Radiation model. A detailed numerical simulation setups and various analyses are provided, including grid independency analysis, initial condition, time step sizes and external boundary conditions. Three different weekend day intermittent operation strategies are investigated. The results showed that Case 3 designed with pre-heating of 20?h has better performance compared to Case 1 designed with pre-heating of 8?h and Case 2 designed with pre-heating of 14?h. The average indoor air temperature differences of approximate 2.1, 1.6 and 1.2 K are observed for Case 1, Case 2 and Case 3, respectively, when comparing two-time slot at 8:00am on Friday morning and Monday morning. This significantly highlights the effect of thermal inertia and the potential of energy saving due to the utilization of intermittent operation. Therefore, the current study presents numerical simulation potential in evaluating the radiant floor heating effects on indoor thermal environment, taking into account building thermal inertia and transient external climatic conditions.     

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.     

太赫兹脉冲焦平面成像技术的发展与应用

作为太赫兹技术中的重要组成部分,太赫兹脉冲焦平面成像一经问世就引起了行业内的广泛关注,人们引入了各种方法去提升此成像技术的测量性能,同时也尝试将此成像技术应用于不同的工业和基础研究领域。本文综述了近年来人们对太赫兹脉冲焦平面成像的技术改良和应用研究,包括提升成像系统的空间分辨率、信噪比、信息获取能力,以及将此成像技术应用于光谱识别检测、超表面器件功能验证、太赫兹特殊光束测量、太赫兹表面波观测等,希望该综述能够推动太赫兹脉冲焦平面成像的进一步技术革新和应用拓展。