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World Congress on intelligent Control and Automation

作者： Shoubiao Tan Lingyu Hu Anqi Wang-Xu Jun Tang Zhaohong Jia Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University School of Electronics and Information Engineering Anhui University

ISBN: (纸本)9781467384155

Cross-modal hashing has received more and more attention because of its fast query speed and low storage cost. In this paper, we propose a flexible yet simple cross-modal hashing method to deal with the problem of cross-modal retrieval. The proposed method consists of two steps. In the first phase, we use a kernel canonical correlation analysis method named Anchor kernel canonical correlation analysis (AKCCA) to map data from different modalities into a common kernel space. In the second phase, we use the method named Supervised Hashing with Kernels (KSH) to learn hashing functions bit by bit. These two useful ingredients are combined seamlessly to achieve promising results. Experimental results on a benchmark dataset demonstrate that our method performs better than several state-of-the-art methods.

关键词： Cross-modal hashing Seeds second phase multivariate analysis Kernel

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Two-weight codes and second order recurrences ∗

arXiv

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arXiv 2017年

作者： Shi, Minjia Zhang, Zhongyi Solé, Patrick Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University No. 3 Feixi Road HefeiAnhui Province230039 China School of Mathematical Sciences Anhui University Hefei230601 China School of Wendian Anhui University Hefei230601 China CNRS/LAGA University of Paris 8 2 rue de la Liberté Saint-Denis93 526 France

Cyclic codes of dimension 2 over a finite field are shown to have at most two nonzero weights. This extends a construction of Rao et al (2010). We compute their weight distribution, and give a condition on the roots o... 详细信息

关键词： Codes (symbols)

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Cross-Layer Power Allocation Scheme for Wireless Full Duplex Relaying System

Cross-Layer Power Allocation Scheme for Wireless Full Duplex...

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2016 8th IEEE International Conference on Communication Software and Networks(ICCSN 2016)

作者： Mengmeng He Yanjun Hu Hui Zhi Quan Yuan Key Lab of Intelligent Computing and Signal Processing Ministry of Education School of Electronics and Information Engineering Anhui University

In this paper,we propose a cross-layer power allocation scheme over wireless relay networks for quality-of-service(Qo S)*** formulate our original throughput maximization problem into effective capacity maximization problem by applying information theory and the concept of the effective *** our scheme,we focus on full duplex mode and amplify-and-forward(AF)*** particular,our proposed scheme derives closed-form expressions and analyzes the impacts of the SNR of the interference channel on the performance of full duplex relaying *** comparison purpose,we also give the analysis of half duplex relaying *** results show that our proposed power allocation scheme can support diverse Qo S guarantees and achieve better effective capacity than equal power allocation scheme and direct transmission *** analysis also indicate that the perfect full duplex mode can achieve twice optimal effective capacity of the half duplex mode.

关键词： power allocation scheme effective capacity full duplex quality-of-service(Qo S) amplify-and-forward(AF)

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Cross-Layer Power Allocation Scheme for Two-Way Amplify-and-Forward Relaying System

Cross-Layer Power Allocation Scheme for Two-Way Amplify-and-...

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2016 8th IEEE International Conference on Communication Software and Networks(ICCSN 2016)

作者： Quan Yuan Yanjun Hu Hui Zhi Mengmeng He Key Lab of Intelligent Computing and Signal Processing Ministry of Education School of Electronics and Information Engineering Anhui University

Two-way relaying can considerably improve spectral efficiency in relay-assisted bidirectional ***,most existing works focus on physical layer to exploit its resource *** benefits and flexible structures of two-way relaying on datalink layer are much less *** in this paper,the cross-layer optimization for amplify-and-forward(AF)two-way relaying system is studied and an optimal power allocation scheme is *** goal is to find the optimal power allocation factors to maximize the weighted sum effective capacity of two sources in the physical layer while guaranteeing the statistical delay quality-of-service(QoS)requirement for each source in the datalink *** statistical delay Qo S requirement is characterized by the QoS exponentq,which is the only requested information exchanged between the physical layer and the datalink layer in our cross-layer design based *** integrating the concept of effective capacity,the cross-layer optimization problem is equivalent to a weighted sum effective capacity maximization *** problem is formulated into a convex optimization problem,and an algorithm is presented to solve this *** results show that proposed optimal power allocation scheme can achieve better weighted sum effective capacity than equal power allocation scheme and direct transmission scheme,and the relay transmission combined with direct links can get the max weighted sum effective capacity.

关键词： two-way relaying quality-of-service(Qo S) cross-layer optimization power allocation effective capacity

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Detecting coordinated regulations of pathways by higher logic analysis

Detecting coordinated regulations of pathways by higher logi...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yansen Su Xingyi Zhang Linqiang Pan Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781509016129

Non-small cell lung cancer (NSCLC) is a malignant tumor, and contains three major subtypes which are difficult to be distinguished at early stages of NSCLC. Many pathways work together to perform certain functions in cells. One might expect the high level of co-appearance or repression of pathways to distinguish different subtypes of NSCLC. However, it is difficult to detect coordinated regulations of pathways by existing methods. In our work, the coordinated regulations of pathways are detected using modified higher logic analysis of gene expression data. Specifically, we identify the genes whose regulation obeys a logic function by the modified higher logic analysis, which focuses on the relationships among the gene triplets that are not evident when genes are examined in a pairwise fashion. Then, the relationships among genes are mapped to pathways to predict the coordinated regulated relationships among pathways. By comparing coordinated regulations of pathways, we find that the regulation patterns of pathways which are associated with cell death are different in three subtypes of NSCLC. This method allows us to uncover co-appearance or repression of pathways in high level, and it has a potential to distinguish the subtypes for complex diseases.

关键词： Cancer Lungs

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A New Method to Parallel Implementation for Batching Vast Small-scale computing Tasks Based on GPU

A New Method to Parallel Implementation for Batching Vast Sm...

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IEEE Conference on Industrial Electronics and Applications

作者： Jun Zhu Haifeng Yao Tao Yang Qiaomei Zhou Kai Li Key laboratory of Intelligent Computing & Signal Processing (Anhui University) Ministry of Education Technology and Innovation Department Shanghai Research Center for Wireless Communications

ISBN: (纸本)9781467386456

The calculation of small-scale data is commonly used in scientific computing and application domain, and the high-efficiency method of small calculation can give play to the potency of many calculation and application. In this paper, a novel self-adaptive parallel computing method based on the graphics processing unit (GPU) architecture for batches of small scale computing tasks is proposed herein. It also provides two other implementation methods, which are the CPU algorithm and the traditional GPU algorithm, and then compares the efficiency of the three schemes. The experimental results show that the implementation efficiency of this new method on the GPU is better than that of method executed by the CPU and that of the traditional GPU algorithm for batching small-scale computing tasks. And this new approach is furthest utilizing the GPU resources, while a large amount of data is processed.

关键词： Small-scale GPU Batch processing Adaptation Parallel

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A New Acquisition Method Based on Differential Correlation

A New Acquisition Method Based on Differential Correlation

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2016 8th IEEE International Conference on Communication Software and Networks(ICCSN 2016)

作者： Sujuan Shang Yanjun Hu Jufeng Luo Yingguan Wang Key laboratory of Intelligent Computing & Signal Processing (Anhui University) Ministry of Education Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences

Acquisition is a key technology in DSSS *** differential correlation is usually employed to eliminate the effect of frequency ***,as the length of pseudo-code grows and the decrease of the SNR,the traditional differential acquisition algorithms will result in great loss of *** paper presents an improved differential acquisition method,named as M-orders Auto-Correlation based on Differential correlation（MAC-DF）.In the proposed method,the input signal is multiplied by the complex conjugate of the pseudo-code to eliminate its *** that,the product is applied to the M-orders Auto-Correlation to compensate the SNR loss caused by the differential *** means of mathematical model to analyze its acquisition *** compare MAC-DF acquisition algorithm with the differential coherent and non-coherent acquisition algorithms through *** simulation results indicate that this algorithm is approximately 5-6dB superior to the traditional differential acquisition algorithms in improving acquisition sensitivity and more adaptive to work under low SNR.

关键词： DSSS Pseudo-code acquisition low SNR differential correlation acquisition algorithm

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Direct optimization of partial AUC with tighter non-convex loss

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Journal of Computational and Theoretical Nanoscience 2016年第1期13卷 928-935页

作者： Cheng, Fan Wang, Ying Wang, Jingsong Liao, Tiantian Zhen, Bowen Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui Province230039 China School of Computer Anhui University Hefei230039 China

Partial AUC is a popular performance metric used in many applications such as bioinformatics and biometrics. Optimizing this measure directly is often challenging since no close form solution exists. In recent work, Narasimhan et al. proposed two general SVM based approaches for optimizing the partial AUC in an arbitrary false positive range αβ. The approaches make use of a cutting plane solver based on the structural hinge loss, and a variety of real-world tasks demonstrate the approaches' effectiveness. However, the algorithms have one disadvantage that they are sensitive to the outliers. To fill the gap, in this paper, we propose a new support vector method with tighter ramp loss, which is capable of suppressing these undesirable effects. The algorithm adopts the structural SVM as framework, and defines the objective function based on the non-convex ramp loss. For the problem that the new objective function is neither convex nor smooth, we present to introduce the CCCP for non-convex approximating and use bundle method for the convex optimization. Numerical experiments on different data sets show that the algorithm we proposed is robust to the outliers, and can yield a more accurate model than the existing baseline approaches. © 2016 American Scientific Publishers All rights reserved.

关键词： Convex optimization

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Protein folding kinetic order prediction from amino acid sequence based on horizontal visibility network

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Current Bioinformatics 2016年第2期11卷 173-185页

作者： Zhao, Zhi-Qin Yu, Zu-Guo Anh, Vo Wu, Jing-Yang Han, Guo-Sheng Hunan Key Laboratory for Computation and Simulation in Science and Engineering and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University XiangtanHunan411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 BrisbaneQ4001 Australia School of Science Xi’an Shiyou University 18 Second Dianzi Road Yanta District Xi’anShaanxi710065 China

Protein folding is one of the most important problems in molecular biology. The kinetic order of protein folding is one of the main aspects of the folding process. Previous methods for predicting protein folding kinetic order require to use the information on tertiary or predicted secondary structure of a protein. In this paper, based on physicochemical properties of amino acids, we propose an approach to predict the protein folding kinetic order from the primary structure of a protein using support vector machine combined with principal component analysis. The horizontal visibility network, Hilbert-Huang transform, global descriptor, and Lempel-Ziv complexity are used to extract features in our approach. To evaluate our approach, the leave-one-out cross-validation test is employed on two widely-used data sets ("IvankovData" and "ZhengData" data sets) consisting of two-state and multi-state proteins. The overall accuracies of prediction can reach 83.87% for "IvankovData" data set and 85% for "ZhengData" data set respectively. Comparisons with the existing methods show that the present approach performs better on the "IvankovData" data set. These results indicate that the present approach is effective and valuable for predicting protein folding kinetic order. Based on factor analysis, we find that the length of protein sequence, hydrophobicity and hydrophilicity of amino acids are important features in our approach. © 2016 Bentham Science Publishers

关键词： Hilbert-Huang transform

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A new modified differential evolution for global optimisation

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International Journal of Wireless and Mobile computing 2016年第1期10卷 56-61页

作者： You, Xuemei Ma, Yinghong Liu, Zhiyuan School of Management Science and Engineering Shandong Normal University Jinan250014 China Key Laboratory of Intelligent Computing Signal Processing Ministry of Education Anhui University Hefei230039 China

Differential evolution (DE) is a population-based random optimisation algorithm, which has been used to solve benchmark functions and real-world optimisation problems. The DE has three important operators: mutation, crossover, and selection. The mutation operator in the original DE can hardly balance the exploitation and exploration of the search. In this paper, we design a new mutation operator to improve the exploitation ability of DE. Experiments are carried out on 13 classical test functions. Simulation results show that the new mutation scheme can help DE to find better solutions than three other classical DE mutation strategies. © Copyright 2016 Inderscience Enterprises Ltd.

关键词： Global optimization

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