Model falsification using set‐valued observers for a class of discrete‐time dynamic systems: a coprime factorization approach

This article introduces a new method for model falsification using set‐valued observers, which can be applied to a class of discrete linear time‐invariant dynamic systems with time‐varying model uncertainties. In comparison with previous results, the main advantages of this approach are as follows: The computation of the convex hull of the set‐valued estimates of the state can be avoided under certain circumstances; to guarantee convergence of the set‐valued estimates of the state, the required number of previous steps is at most as large as the number of states of the nominal plant; and it provides a straightforward nonconservative method to falsify uncertain models of dynamic systems, including open‐loop unstable plants. The results obtained are illustrated in simulation, emphasizing the advantages and shortcomings of the suggested method. Copyright © 2013 John Wiley & Sons, Ltd.     

An automatic 2D to 3D video conversion approach based on RGB-D images

3D movies/videos have become increasingly popular in the market; however, they are usually produced by professionals. This paper presents a new technique for the automatic conversion of 2D to 3D video based on RGB-D sensors, which can be easily conducted by ordinary users. To generate a 3D image, one approach is to combine the original 2D color image and its corresponding depth map together to perform depth image-based rendering (DIBR). An RGB-D sensor is one of the inexpensive ways to capture an image and its corresponding depth map. The quality of the depth map and the DIBR algorithm are crucial to this process. Our approach is twofold. First, the depth maps captured directly by RGB-D sensors are generally of poor quality because there are many regions missing depth information, especially near the edges of objects. This paper proposes a new RGB-D sensor based depth map inpainting method that divides the regions with missing depths into interior holes and border holes. Different schemes are used to inpaint the different types of holes. Second, an improved hole filling approach for DIBR is proposed to synthesize the 3D images by using the corresponding color images and the inpainted depth maps. Extensive experiments were conducted on different evaluation datasets. The results show the effectiveness of our method.

     

GPU-based parallel Shadow Features generation at neural system for improving gait human activity recognition

Multimedia Tools and Applications - In this paper, we propose a new method for improving human activity recognition (HAR) datasets in order to increase their classification accuracy when trained...     

A systematic literature review on intelligent automation: Aligning concepts from theory,practice, and future perspectives

With the recent developments in robotic process automation (RPA) and artificial intelligence (AI), academics and industrial practitioners are now pursuing robust and adaptive decision making (DM) in real-life engineering applications and automated business workflows and processes to accommodate context awareness, adaptation to environment and customisation. The emerging research via RPA, AI and soft computing offers sophisticated decision analysis methods, data-driven DM and scenario analysis with regard to the consideration of decision choices and provides benefits in numerous engineering applications. The emerging intelligent automation (IA) – the combination of RPA, AI and soft computing – can further transcend traditional DM to achieve unprecedented levels of operational efficiency, decision quality and system reliability. RPA allows an intelligent agent to eliminate operational errors and mimic manual routine decisions, including rule-based, well-structured and repetitive decisions involving enormous data, in a digital system, while AI has the cognitive capabilities to emulate the actions of human behaviour and process unstructured data via machine learning, natural language processing and image processing. Insights from IA drive new opportunities in providing automated DM processes, fault diagnosis, knowledge elicitation and solutions under complex decision environments with the presence of context-aware data, uncertainty and customer preferences. This sophisticated review attempts to deliver the relevant research directions and applications from the selected literature to the readers and address the key contributions of the selected literature, IA’s benefits, implementation considerations, challenges and potential IA applications to foster the relevant research development in the domain.     

Hierarchical control for cornering stability of dual-motor RWD vehicles with electronic differential system using PSO optimized SOSMC method

This paper proposes a novel control scheme with a three-layer hierarchical structure to improve the cornering stability of the dual-motor rear-wheel drive (RWD) vehicles with the electronic differential system (EDS). The proposed hierarchical structure for the control system includes the observing layer, control layer, and actuation layer. In the observing layer, the driver model is designed to obtain the nominal steering angle, and the state observer is designed to obtain the yaw angle which cannot be easily measured. Then, particle swarm optimization (PSO) and second order sliding mode control (SOSMC) are employed in the control layer. The SOSMC part is used to design the control law to eliminate the chattering problem in the sliding mode algorithm, and the PSO part is used to obtain the optimal weights in the sliding mode surface to meet the minimum sideslip angle error and yaw rate error. The actuation layer allocates the corrected yaw moment by distributing the driving force to each independent driving wheel. Finally, the numerical tests are carried out under the double line change (DLC) maneuver. The results show that the proposed control system can effectively improve the cornering stability of the dual-motor RWD vehicles and reduce their motor power consumption.     

Sunway supercomputer architecture towards exascale computing: analysis and practice

Science China Information Sciences -     

西藏牛皮消的化学成分研究

从西藏牛皮消(Cynanchum saccatum)乙醇提取物的乙酸乙酯萃取部位分离出13个化合物,通过理化性质和波谱分析,分别鉴定为对羟基苯乙酮(1)、3,4-二羟基苯乙酮(2)、2,4-二羟基苯乙酮(3)、2,5-二羟基苯乙酮(4)、白首乌二苯酮(5)、3,5-二羟基苯甲酸甲酯(6)、对羟基苯甲酸(7)、2,5-二羟基苯甲酸甲酯(8)、3,3'-二甲氧基-4,9,9'-三羟基-苯并呋喃木脂素-7'-烯-9-O-β-D-吡喃葡萄糖苷(9)、加加明3-O-β-D-加拿大麻吡喃糖基-(1→4)-β-D-夹竹桃吡喃糖基-(1→4)-β-D-夹竹桃吡喃糖苷(10)、青阳参苷元3-O-β-D-加拿大麻吡喃糖基-(1→4)-β-D-加拿大麻吡喃糖基-(1→4)-β-D-夹竹桃吡喃糖基-(1→4)-β-D-加拿大麻吡喃糖苷(11)、β-谷甾醇(12)和β-胡萝卜苷(13).其中化合物9为首次从鹅绒藤属中分离得到,化合物1--3、5--8、10、11、13为首次从该植物中分离得到.     

重庆方言的两个零形否定结构

在重庆方言中,“X＋（个）＋Y”和“X＋（才）＋Y”两个结构并不含有否定词,却能表达否定概念,属于零形否定现象.这两个结构使用环境十分丰富,能表达多种语用意义,而且在话语、语用及语法等方面都存在诸多特点.在来源问题上,“X＋（个）＋Y”结构由“X一个Y”经过缩减、类推等步骤形成,而两种类型的“X＋（才）＋Y”结构的产生,则是分别源于具有反常特征的X导致的语用效果,以及副词“才”和形容词“怪”的词汇化演变.     

Hierarchical classification in text mining for sentiment analysis of online news

Sentiment analysis in text mining is a challenging task. Sentiment is subtly reflected by the tone and affective content of a writer’s words. Conventional text mining techniques, which are based on keyword frequencies, usually run short of accurately detecting such subjective information implied in the text. In this paper, we evaluate several popular classification algorithms, along with three filtering schemes. The filtering schemes progressively shrink the original dataset with respect to the contextual polarity and frequent terms of a document. We call this approach “hierarchical classification”. The effects of the approach in different combination of classification algorithms and filtering schemes are discussed over three sets of controversial online news articles where binary and multi-class classifications are applied. Meanwhile we use two methods to test this hierarchical classification model, and also have a comparison of the two methods.