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Information Fusion
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#1Aoi Honda (Deakin University)
#2Simon James (Deakin University)H-Index: 14
Abstract Developments in the learning and interpretation of fuzzy integrals have paved the way for a myriad of applications in data analysis and prediction. The ability of the associated fuzzy measure to model heterogeneous interactions allow high flexibility when it comes to data fusion tasks – comparable to that of neural networks – however the fuzzy integral structure and properties also afford a degree of robustness and interpretability not enjoyed by such tools. On the other hand, neural ne...
#1Xiaoqiang Yan (Zhengzhou University)H-Index: 2
#2Yangdong Ye (Zhengzhou University)H-Index: 7
Last.Hui Yu (University of Portsmouth)H-Index: 9
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Abstract Multi-view and ensemble clustering methods have been receiving considerable attention in exploiting multiple features of data. However, both of these methods have their own set of limitations. Specifically, the performance of multi-view clustering may degrade due to the conflict between heterogeneous features, while ensemble clustering relies heavily on the quality of basic clusterings since it discovers the final clustering partition without considering the original feature structures ...
#1Ke Li (Sichuan University)
#2Haiming Liang (Sichuan University)H-Index: 5
Last.Yucheng Dong (Sichuan University)H-Index: 35
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Abstract In opinion dynamics, some agents may exhibit the cognitive dissonance behaviors owing to the contradictory belief, attitudes and opinions that they might confront with. This may greatly influence the evolutions of opinions and connections. To this end, this paper proposes an opinion dynamics model based on the cognitive dissonance (ODCD). In the ODCD model, with the consideration of bounded confidence effects, the methods for updating the opinions and network of agents are provided, res...
#1Xiao Wei Sun (Hefei University of Technology)H-Index: 65
#2Jia Li (Hefei University of Technology)
Last.Jianhua Tao (CAS: Chinese Academy of Sciences)
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Abstract In recent years, the generation of conversation content based on deep neural networks has attracted many researchers. However, traditional neural language models tend to generate general replies, lacking logical and emotional factors. This paper proposes a conversation content generation model that combines reinforcement learning with emotional editing constraints to generate more meaningful and customizable emotional replies. The model divides the replies into three clauses based on pr...
#1Ran Liu (SUTD: Singapore University of Technology and Design)H-Index: 5
#2Chau Yuen (SUTD: Singapore University of Technology and Design)H-Index: 38
Last.U-Xuan Tan (SUTD: Singapore University of Technology and Design)H-Index: 15
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Abstract Positioning between multiple users without any given infrastructure is essential for many applications, such as emergency response in disaster areas. Traditional approaches based on inertial-measurement units (IMU) are able to measure position changes without any reference, but the accuracy deteriorates due to error accumulation for long terms. Particularly, it is challenging to deal with irregular walking patterns of users. This paper proposes to combine IMU and radio measurements (i.e...
#1Jing Zhang (Fujian University of Technology)H-Index: 1
#2Zhiwei Lin (Ulster University)H-Index: 5
Last.Li Xu (Fujian Normal University)H-Index: 16
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Abstract Data aggregation is one of the essential and fundamental processes in Wireless Sensor Networks (WSNs). When and how to gather data from the sensors to the sink has a direct impact on the lifetime of the WSNs because the energy consumption is proportion to the frequency of data transmission. In general, sensors in a WSN are randomly distributed for creating a massive coverage WSN environment within a short period. Because the sensors nearby the sink are responsible for more data forwardi...
#1Zelin Wang (Decision Sciences Institute)
#2Yingming Wang (FZU: Fuzhou University)H-Index: 3
Last.Ying-Ming Wang (FZU: Fuzhou University)H-Index: 4
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Abstract Linguistic distribution assessments with probabilistic information are a flexible means to express the opinions of decision makers (DMs) with importance degree of each linguistic term. Therefore, research on multi-attribute group decision making (MAGDM) problems with linguistic distribution assessments is increasing. However, the probability distribution is usually only partially known. In order to obtain the complete probability distribution information, we propose the concept of stoch...
#1Ashish V. Vanmali (IITB: Indian Institute of Technology Bombay)H-Index: 2
#2Tushar Kataria (IITB: Indian Institute of Technology Bombay)
Last.Vikram M. Gadre (IITB: Indian Institute of Technology Bombay)H-Index: 13
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Abstract In this paper, we investigate an issue of the ringing artifacts inherent to wavelet based image fusion. A thorough analysis of the ringing phenomenon, by experimenting with different types of images and different wavelet families, with varying lengths of filters and varying levels of decomposition is performed to obtain deeper insights of the ringing artifacts. It is experimentally shown that wavelet based fusion results in the modification of the intra- and inter-scale dependencies, wi...
#1Han Qiu (ENST: Télécom ParisTech)
#2Meikang Qiu (Columbia University)
Last.Zhihui Lu (Fudan University)
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Abstract Body Sensor Networks (BSNs) are developing rapidly in recent years as it combines the Internet-of-Things (IoT) and data analytic techniques for building a remote healthcare system. However, as BSNs are implemented on the existing wireless communication systems, the security and privacy in the BSN are facing many challenges. Performing standard encryption schemes on the health data before outsourcing at the sensors’ ends are not suitable for this BSN environment as it is costly both in e...
#1Yuxuan Shen (Donghua University)H-Index: 1
#2Zidong Wang (Brunel University London)H-Index: 99
Last.Fuad E. Alsaadi (KAU: King Abdulaziz University)H-Index: 35
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Abstract In this paper, the fusion estimation problem is studied for a class of discrete time-varying multi-rate linear repetitive processes (LRPs) under weighted try-once-discard protocol. The LRPs are measured by multiple sensors that are allowed to have different sampling periods, and the state updating period of the LRPs is also allowed to be different from the sampling periods of the asynchronous sensors. To facilitate the estimator design, the lifting technique is applied to transform the ...
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