关键词：
Community detection;Multi-similarity;Vertex feature;Social network;K-means clustering
摘要：
Social network detection and identification constitute an important topic in the field of sociology. Previous graph similarity has focus on either the topological structure of graph or the feature value of vertex. In this work, a multi-similarity measure method for community is described. The approach devised by using multi-similarity properties based on vertex features, relationship density and topology structure, and therefore is can be formulated and extended to practical implementation. The framework of community detection combines K-means clustering, spectral clustering and modularity algorithm-making it an effective basis for the realization of a social network interpretation. With this scheme, three evaluation criteria are proposed for methodology determination. The experimental results show a better working performance of the recommended method than traditional algorithms via statistical analysis.
期刊：
IPSJ Transactions on Bioinformatics,2019年12:1-8 ISSN：1882-6679
作者机构：
Department of Information Technology, Hunan Women's University, China;College of Information and Electronic Engineering, Hunan City University, China
关键词：
Information entropy;Ovarian cancer;microRNA regulatory module
摘要：
This paper presents the development of wearable sensing system that can be used to study the gait dynamics of human. A tester wearing sensing shoes participates in this study. Human gait information about standing, jumping and walking is obtained as prior probability based on the train movement model setup theory. For feature extraction of gait, five kinds of features are extracted from foot pressure signals, which are subsequently used for motion analysis. We employ support vector machine and fractal analysis for gait recognition and test the identification performance. Testing outcomes indicate an overall accuracy of 93.57% via radial basis function kernel function. These results demonstrate considerable potential in gait identification.
摘要：
Unstructured online reviews are undergoing a rather rapid expansion with the development of E-commerce, and they contain sentiment information in which consumers and businesses are very interested. Therefore, effective sentiment classification has become one of the important research topics. Many studies have shown that ensemble learning methods may have great hopeful applicability in sentiment classification tasks. In this paper, we propose a new ensemble learning framework for sentiment classification of Chinese online reviews. First of all, according to the complicated characteristics of Chinese online reviews, we extract Part of Speech Combination Pattern, Frequent Word Sequence Pattern and Order Preserved Submatrix Pattern as the input features. Furthermore, we use the algorithm of Random Subspace based on Information Gain by considering the problem of massive features in the reviews, which can improve the base classifiers simultaneously. Finally, we adopt the algorithm of Constructing Base Classifiers based on Product Attributes to combine the sentiment information of each attribute in a review so as to obtain better performance on sentiment classification. The experimental results show that the proposed ensemble learning framework has significant improvement in sentiment classification of Chinese online reviews.
通讯机构：
Key Laboratory of Forestry Remote Sensing Based Big Data and Ecological Security for Hunan Province, Central South University of Forestry and Technology, Changsha, China
期刊：
IEEE INTERNET OF THINGS JOURNAL,2019年6(1):718-733 ISSN：2327-4662
通讯作者：
Qin, Hua
作者机构：
[Qin, Hua; Cao, Buwen; Zeng, Min; Chen, Weihong] Hunan City Univ, Coll Informat & Elect Engn, Yiyang 413000, Peoples R China.;[Li, Jessica; Peng, Yang] Univ Washington, Div Comp & Software Syst, Bothell, WA 98011 USA.
通讯机构：
[Qin, Hua] H;Hunan City Univ, Coll Informat & Elect Engn, Yiyang 413000, Peoples R China.
关键词：
Dual radio;energy efficiency;Internet of Things (IoT);pipeline
摘要：
The future Internet of Things (IoT) will enable Internet connectivity for a vast amount of battery-powered devices, which usually need to communicate with each other or to some remote gateways through multihop communications. Although ZigBee has become a widely used communication technology in IoT, Wi-Fi, on the other hand, has its unique advantages such as high throughput and native IP compatibility, despite its potentially higher energy consumption. With the development of IoT, more and more IoT devices are equipped with multiple radio interfaces, such as both Wi-Fi and ZigBee. Inspired by this, we propose a dual-interface dual-pipeline scheduling (DIPS) scheme, which leverages an activation pipeline mainly constructed by low-power ZigBee interfaces to wake up a data pipeline constructed by high-power Wi-Fi interfaces on demand, toward enabling multihop data delivery in IoT. The objective is to minimize network energy consumption while satisfying certain end-to-end delay requirements. Extensive simulations and prototype-based experiments have been conducted. The results show that the energy consumption of DIPS is 96.5% and 92.8% lower than that of the IEEE 802.11's standard power saving scheme and a state-of-the-art pipeline-based scheme in moderate traffic scenarios, respectively.
摘要：
Community discovery algorithms are important aspects of network science, especially as social network structures become more complex. Multi-mode social networks have recently become a challenging and popular topic in this field. At present, inner-mode relationship is mainly considered in community discovery algorithms for social networks. Thus, the effect of the these methods is not well in clustering as the intra-mode relationship is not considered in the clustering methods. In this paper, we propose a flexible and robust clustering framework, MRTA (the Multi-Similarity Regular Tri-Factorization Algorithm), based on non-negative tri-matrix factorization. MRTA has several advantages over the existing methods. First, it achieves more consistent clustering results based on cluster indicator of inner-mode and intra-mode relationships of multi-mode networks. Second, it can simultaneously cluster multiple modes, which is impossible for single-mode clustering algorithms. Finally, it provides a multi-mode clustering solution that is more robust to noise. We perform an efficient iterative update algorithm, and theoretically prove its accuracy. Extensive experimental results of a variety of real and synthetic networks demonstrate the effectiveness of our approach.
通讯机构：
[He, Longhui] C;[He, Longhui] H;Cent S Univ, Sch Phys & Elect, Changsha 410083, Hunan, Peoples R China.;Hunan City Univ, Coll Informat & Elect Engn, Yiyang 413000, Peoples R China.
关键词：
P band;Metamaterial absorber;Dual-peak absorption;Magnetic metal
摘要：
In order to investigate the effect of magnetic metal on the absorption performance of metamaterial absorber (MMA), a dual-peak MMA based on magnetic metal nickel is designed and demonstrated in the P-band (300–1000 MHz). Two-layer square-ring-metal resonator arrays and two-layer dielectric substrates are arranged alternately with each other to constitute the proposed dual-peak MMA backed with a reflective metal plate. The influences of copper or nickel metallic layers on the absorption coefficients are comparatively analyzed. For the nickel MMA, the dual-peak absorption coefficients of 99.82% and 99.09% are achieved at 394 MHz and 605 MHz, respectively. Moreover, the thickness of dual-peak MMA could be reduced to 9 mm by employing magnetic metal nickel. The physical mechanism of dual-peak absorption is illustrated by surface current distributions, magnetic field distributions and power loss density distributions. The relationship between the changes of geometric dimensions and the shift of peak absorption frequencies is ultimately discussed. These results could provide instructive guidance for realizing a thin dual-peak MMA in the P-band.
期刊：
Modern Physics Letters B,2019年33(6):1950057 ISSN：0217-9849
通讯作者：
He, Longhui
作者机构：
[He, Jun; Shan, Dongyong; He, Longhui; Xu, Hui] Cent S Univ, Sch Phys & Elect, Changsha 410083, Hunan, Peoples R China.;[Ghen, Zhiquan; He, Longhui] Hunan City Univ, Sch Commun & Elect Engn, Yiyang 413000, Peoples R China.;[Liu, Sheng] Hunan Inst Engn, Sch Mech Engn, Xiangtan 411104, Peoples R China.
通讯机构：
[He, Longhui] C;[He, Longhui] H;Cent S Univ, Sch Phys & Elect, Changsha 410083, Hunan, Peoples R China.;Hunan City Univ, Sch Commun & Elect Engn, Yiyang 413000, Peoples R China.
关键词：
Metamaterial perfect absorber;square ring structure;low frequency;magnetic metal
摘要：
A metal-dielectric-metal (MDM) sandwich metamaterial perfect absorber (MPA) with magnetic nickel metal has been designed. An optimal absorption of 99.28% at 404 MHz is achieved for MPA with thickness of 5.54 mm. Resonant absorption is demonstrated to be main mechanism according to analyses on surface current distributions and electromagnetic field distributions. Furthermore, the electromagnetic energy is mainly dissipated in magnetic metal with magnetic loss proportion of 55.43% by comparatively analyzing the wave-absorbing performance of using magnetic metal, non-magnetic metal and perfect electric conductor (PEC) as metallic layers. These results would provide a guidance for the design of quasi-microwave absorbing/shielding materials.
