JUSTC

Marcinkiewicz type complete convergence for weighted sums under sub-linear expectations

YU Donglin, WU Qunying

2018, 48(2): 89-96. doi: 10.3969/j.issn.0253-2778.2018.02.001

Abstract:
The complete convergence theorems under sub-linear expectations was studied. As applications, Marcinkiewicz type complete convergence for weighted sums of END random

MacWilliams identities of linear codes with respect to RT metric over Mn×s(F l+v F l+…+vk-1 l)

WU Rongsheng, SHI Minjia, DING Shuangshuang

2018, 48(2): 97-104. doi: 10.3969/j.issn.0253-2778.2018.02.002

Article Views:522 Full article PDF

Abstract:
A new Gray map over the commutative ring R=

An algorithm for computing all the critical points of exponent periodic sequences

TANG Miao, WANG Juxiang

2018, 48(2): 105-110. doi: 10.3969/j.issn.0253-2778.2018.02.003

Article Views:502 Full article PDF

Abstract:
The k-error linear complexity of periodic sequences is an important security indice of stream cipher systems. The k-error linear complexity decreases as the number of errors k increases, that the critical points are those where a decrease occurs in the k-error linear complexity. The pn periodic sequences over the finite field GF(pm) were focused upon， where p is a prime. Some properties of the k-error linear complexity were discussed, and an algorithm was presented for computing all the critical points for a given sequence.

An SIQR mode with impulsive vaccination and impulsive elimination

MA Yanli, ZHANG Zhonghua, LIU Jiabao, DING Jian

2018, 48(2): 111-117. doi: 10.3969/j.issn.0253-2778.2018.02.004

Article Views:572 Full article PDF

Abstract:
Impulsive vaccination, impulsive elimination and quarantine strategies were considered in an SIQR epidemic model. The dynamical behavior of an SIQR epidemic model was discussed both theoretically and numerically. Firstly, the disease-free T periodic solution and the basic reproductive number R0 were obtained. Secondly, the local asymptotic stability of the disease-free T periodic solution with Floquet theorem was proved and the global asymptotic stability of the disease-free T periodic solution was also proved by impulsive differential equation. Thirdly, numerical simulation was conducted to illustrate the

An arbitrage strategy model for ferrous metal futures based on LSTM neural network

LONG Aoming, BI Xiuchun, ZHANG Shuguang

2018, 48(2): 125-132. doi: 10.3969/j.issn.0253-2778.2018.02.006

Article Views:1316 Full article PDF

Abstract:
Using the cointegration test method and LSTM neural network algorithm, the arbitrage strategy model for ferrous metal futures market was established. The empirical study is conducted on the coke futures, iron ore futures on the Dalian Commodity Exchange and the rebar futures on the Shanghai Futures Exchange using the arbitrage strategy model based on LSTM neural network. The arbitrage strategy models based on LSTM neural network, BP neural network and convolutional neural network were compared, and the empirical results show that the arbitrage strategy model for ferrous metal futures based on LSTM neural network is feasible and effective, and performs better than the arbitrage strategy models based on BP neural network and convolutional neural network.

A method for aggregating three types of preference relations in group decision making environment

TU Zhenkun, DUAN Chuanqing

2018, 48(2): 133-139. doi: 10.3969/j.issn.0253-2778.2018.02.007

Article Views:542 Full article PDF

Abstract:
Experts often give heterogeneous types of preference information, such as fuzzy preference relations, interval reciprocal preference relations and linguistic preference relations, in a group decision making environment. A new method was developed for aggregating these three types of preference relations, whose basic idea is that different kinds of information are transformed into an intermediate field (an utility space) before they are aggregated. The advantage of this method is that the direct inter-conversion among those different kinds of preference information is avoided and the computation process is more simple. Firstly, considering fuzzy preference relations, interval reciprocal preference relations and linguistic preference relations, these preference relations were transformed into fuzzy preference relations based on the idea of utility, and the reasonability in the transforming process was discussed. Then an approach was provided to aggregate those kinds of information and select the best alternatives in the group decision making process. Finally, the practicability of this method was illustrated with an example.

Perception-aware multi-view rendering optimization for indoor scenes

JI Mengyu, LIU Ligang

2018, 48(2): 140-147. doi: 10.3969/j.issn.0253-2778.2018.02.008

Article Views:523 Full article PDF

Abstract:
Multi-view rendering optimization for indoor scenes in the process of interior design was studied. Given an indoor scene model，firstly，a novel and perception-aware viewpoint metric function that is based on geometry information，structure information and aesthetic information was defined. Secondly，a multi-view objective function was modelled and optimized to obtain a multi-view set by using the simulated annealing algorithm. Extensive experiments show that the proposed method can adaptively obtain a set of all-sided and artistic rendering images for multi-view rendering optimization.

Face color transfer based on optimal transport model

LI Zhenxi, ZHANG Juyong

2018, 48(2): 148-153. doi: 10.3969/j.issn.0253-2778.2018.02.009

Article Views:663 Full article PDF

Abstract:
Existing face color transfer algorithms are only based on Lαβ color space for matching mean and variance, and such transfer is limited to linear transformation and is usually applied to natural images. At the same time, these algorithms usually use facial landmark information to locate facial feature positions. However, the facial feature information thus obtained lacks accuracy and needs further optimization. To address these problems, a new face color transformation method was proposed based on the optimal transfer model to get the natural face color transfer effect. Firstly, the semantic information of the face was obtained directly by using the fully convolution network, and the corresponding face color transfer result was obtained by using the optimal transfer model. Experimental results show that the proposed algorithm is significantly improved in both the robustness of facial features segmentation and the subjective vision of face image color transfer.

Fast cancer diagnosis based on extreme learning machine

LIN Yupeng, XIE Zhige, XU Kai, CHEN Fei, LIU Ligang

2018, 48(2): 154-160. doi: 10.3969/j.issn.0253-2778.2018.02.010

Article Views:595 Full article PDF

Abstract:
The local receptive fields based extreme learning machine (ELM-LRF) method was utilized to learn the effective features from the acquired gene expression data to help enhance cancer diagnosis and classification. Firstly, the principal component analysis (PCA) method was implemented to process the dataset. Secondly, the features mapping to map our dataset were constructed to the specific feature space. Finally, the features to train the learning model were used to get the final ELM feature extraction model. The experiment shows that the proposed algorithm outperforms almost all the existing methods in accuracy and efficiency.

Two-stages marketing strategy of monopoly smart device enterprise

LUO Yi

2018, 48(2): 118-124. doi: 10.3969/j.issn.0253-2778.2018.02.005

Article Views:519 Full article PDF

Abstract:
For a monopoly smart device enterprise, through modeling the two-stages pricing problem of smart devices products under two marketing strategies, the impacts of operating system performance on the optimal prices, market shares and profits of two versions of products were analyzed. At the same time, the difference on enterprise’ total market shares and total profits between two marketing strategies also taken into analysis.

Community detection based on spectral clustering with node attributes

TANG Fengqin, DING Wenwen

2018, 48(2): 162-173. doi: 10.3969/j.issn.0253-2778.2018.02.011

Article Views:774 Full article PDF

Abstract:
A community detection approach (SCSA) based on the spectral clustering method that combines both structural information and node attributes information was proposed.Firstly,the SCSA algorithm converted the node-attributed graph to a weighted graph,where the edge weights are measured by attribute similarities.Then,the spectral clustering was applied on the weighted graph.The SCSA algorithm partitioned a network associated with attributes into K communities in which the nodes are not only well connected but also have similar attributes.Notice that not all attributes are useful in the clustering process,and irrelevant attributes can lower the overall accuracy of community detection by adding noise.To address this issue,an attribute weight self-adjustment mechanism embedded into spectral clustering was proposed in order to improve the community detection quality.Experiments demonstrate the effectiveness of the proposed algorithm.

2018 Vol. 48, No. 2

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