检索结果-内蒙古大学图书馆

arXiv 2019年

作者： Song, Xiaotao Sun, Hailong Wang, Xu Yan, Jiafei School of Software Taiyuan University of Technology China SKLSDE Lab School of Computer Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China

As an integral part of source code files, code comments help improve program readability and comprehension. However, developers sometimes do not comment on their program code adequately due to the incurred extra efforts, lack of relevant knowledge, unawareness of the importance of code commenting or some other factors. As a result, code comments can be inadequate, absent or even mismatched with source code, which affects the understanding, reusing and the maintenance of software. To solve these problems of code comments, researchers have been concerned with generating code comments automatically. In this work, we aim at conducting a survey of automatic code commenting researches. First, we generally analyze the challenges and research framework of automatic generation of program comments. Second, we present the classification of representative algorithms, the design principles, strengths and weaknesses of each category of algorithms. Meanwhile, we also provide an overview of the quality assessment of the generated comments. Finally, we summarize some future directions for advancing the techniques of automatic generation of code comments and the quality assessment of comments. Copyright © 2019, The Authors. All rights reserved.

关键词： Surveys

来源：评论

学校读者我要写书评

暂无评论

An ADMM-based approach to robust array pattern synthesis

arXiv

引用

arXiv 2019年

作者： Yang, Jintai Lin, Jingran Shi, Qingjiang Li, Qiang School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Software Engineering Tongji University Shanghai200092 China Shenzhen Research Institute of Big Data Shenzhen518172 China

In most existing robust array beam pattern synthesis studies, the bounded-sphere model is used to describe the steering vector (SV) uncertainties. In this letter, instead of bounding the norm of SV perturbations as a whole, we explore the amplitude and phase perturbations of each SV element separately, thereby obtaining a tighter SV uncertainty model. Based on this model, we formulate the robust array pattern synthesis problem from the perspective of the min-max optimization, which aims to minimize the maximum side lobe response, while preserving the main lobe response. However, this problem is difficult due to the infinitely many non-convex constraints. As a remedy, we employ the worst-case criterion and recast the problem as a convex second-order cone program (SOCP). To solve the SOCP, we further develop an alternating direction method of multipliers (ADMM)-based algorithm, which is computationally efficient with each step being computed in closed form. Numerical simulations demonstrate the efficacy and efficiency of the proposed algorithm. Copyright © 2019, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Interpretable Prediction of Protein-Ligand Interaction by Convolutional Neural Network

Interpretable Prediction of Protein-Ligand Interaction by Co...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Fan Hu Jiaxin Jiang Peng Yin Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China School of Software Engineering University of Science and Technology of China Hefei China

Evaluation of protein-ligand interaction is a crucial step in the process of drug discovery. Recently, several methods based on deep learning have gained impressive binary classification performance on protein-ligand binding prediction. However, lack of three-dimensional complex data still limits the accuracy and robustness of evaluation of protein-ligand binding affinity, as well as the prediction of their binding sites. In this paper, we propose a novel convolutional neural network based method for estimating the binding affinity between protein and ligand using only 1D sequence data. Even with the same amount of sample size, this model outperforms other structure-dependent traditional and machine learning based methods in terms of both binary classification and regression task. Furthermore, we use this model to identify the key amino acid residues of protein that are vital for binding interaction, which provides biological interpretation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Substrate concentration effect on gene expression in genetic circuits with additional positive feedback

引用

Science China(Technological Sciences) 2018年第8期61卷 1175-1183页

作者： WU LuLu WANG Pei Lü JinHu Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences School of Mathematics and Statistics Henan University School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment and Beijing Advanced Innovation Center for Big Data and Brain Machine Intelligence Beihang University

In gene regulatory networks, gene regulation loops often occur with multiple positive feedback, multiple negative feedback and coupled positive and negative feedback forms. In above gene regulation loops, auto-activation loops are ubiquitous regulatory motifs. This paper aims to investigate a two-component dual-positive feedback genetic circuit, which consists of a double negative feedback circuit and an additional positive feedback loop(APFL). We study effect of substrate concentration on gene expression in the single and the networked systems with APFLs, respectively. We find that substrate concentration can tune stochastic switch behavior in the signal system and then we explore relationship of substrate concentration with positive feedback strength in aspect of stochastic switch behavior. Furthermore, we also discuss gene expression and stochastic switch behavior in the networked systems with APFLs. Based on analysis in the networked systems, we discover that genes express in some specific cells and do not express in the other cells when the expression achieves its steady state. These results can be used to well explain the character of regionalization in the expression of genes and the phenomenon of gene differentiation.

关键词： substrate concentration additional positive feedback loop stochastic switch behavior gene expression gene differ-entiation

来源：评论

学校读者我要写书评

暂无评论

Efficient Block Pruning Based on Kernel and Feature Stablization

Efficient Block Pruning Based on Kernel and Feature Stabliza...

引用

Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Sheng Xu Hanlin Chen Kexin Liu Jinhu Lii Baochang Zhang School of Automatic Science and Electrical Engineering Beihang University China State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University China

With the development of computer vision research, the architecture of convolutional neural network becomes more and more complex to reach the state-of-the-art performance. Is the complexity of the model necessarily proportional to its accuracy? To answer this, the compression of the network has attracted much attention in the academy and industry. Existing network pruning methods mostly rely on the scoring mechanism of complexity or diversity of kernels to compress the network, and then build the network model after removing the kernels by tuning or training on the input data. These methods are cumbersome and depend on a well-trained pre-trained model. In this paper, we propose an end-to-end block pruning method based on kernel and feature stability by pruning blocks efficiently. To accomplish this, we firstly introduce a mask to scale the output of the blocks, and the L1 regularization term to monitor the mask update. Second, we introduce the Center Loss to guarantee that the feature does not deviate greatly during learning. To converge fast, we introduce fast iterative shrinkage-thresholding algorithm (FISTA) to optimize the mask, by which a more fast and reliable pruning process is achieved. We implement experiments on different datasets, including CIFAR-10 and ImageNet ILSVRC2012. All the experiments have achieved the state-of-the-art accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Discriminatively Relabel for Partial Multi-label Learning

Discriminatively Relabel for Partial Multi-label Learning

引用

IEEE International Conference on data Mining (ICDM)

作者： Shuo He Ke Deng Li Li Senlin Shu Li Liu School of Computer and Information Science Southwest University Chongqing China School of Computer Science and Information Technology RMIT University Australia School of Big Data and Software Engineering Chongqing University Chongqing China

Partial multi-label learning (PML) deals with the problem where each training example is assigned multiple candidate labels, only a part of which are correct. To learn from such PML examples, the straightforward model training tends to be misled by the noise candidate label set. To alleviate this problem, a coupled framework is established in this paper to learn the desired model and perform the relabeling procedure alternatively. In the relabeling procedure, instead of simply extracting relative label confidences, or deterministically eliminating low confidence labels and preserving high confidence labels as ground-truth ones, we introduce a soft sign thresholding operator to adaptively strengthen candidate labels with high confidence and weaken candidate labels with low confidence, which enlarges the difference of confidences of candidate labels within allowable range. We further show that the resulting nonconvex quadratic programming (QP) optimization problem can be relaxed into a convex QP problem with proper conditions. Extensive experiments on synthesized and real-world data sets demonstrate the effectiveness of our proposed approach.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Coherent H ∞ control for Markovian jump linear quantum systems

引用

IFAC-PapersOnLine 2020年第2期53卷 269-274页

作者： Yanan Liu Daoyi Dong Ian R. Petersen Qing Gao Steven X. Ding Hidehiro Yonezawa School of Engineering and Information Technology University of New South Wales Canberra ACT 2600 Australia Center for Quantum Computation and Communication Technology Australian Research Council Canberra ACT 2600 Australia Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen. 47057 Duisburg Germany Research School of Electrical Energy and Materials Engineering The Australian National University Canberra ACT 2601 Australia School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing and also with Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China

The purpose of this paper is to design a coherent feedback controller for a Markovian jump linear quantum system suffering from a fault signal. The control objective is to bound the effect of the disturbance input on the output for the time-varying quantum system. We prove the relation between the H ∞ control problem, the dissipation properties, and the solutions of Riccati differential equations, by which the H ∞ controller of the Markovian jump linear quantum system is given by the solutions of Linear Matrix Inequalities (LMIs).

关键词： Coherent quantum feedback H∞ control fault-tolerant control Markovian jump linear quantum systems

来源：评论

学校读者我要写书评

暂无评论

An Overview of Geospatial Information Visualization 6

An Overview of Geospatial Information Visualization

引用

6th IEEE International Conference on Progress in Informatics and Computing, PIC 2018

作者： Zou, Taotao Li, Wenshu Liu, Pengyuan Su, Xianchuang Huang, Hai Han, Yang Guo, Xiaoying College of Information Science and Technology Zhejiang Sci-Tech University Hangzhou China Institute of Big Data Science and Industry School of Software Engineering Shanxi University Taiyuan China

ISBN: (纸本)9781538676707

The geospatial data nowadays are usually large and complex, which call for innovative and easy-to-understand visualization platforms that can reveal meaningful information. Compared with the traditional visual analysis methods, today's visualization technologies have been able to deal with large amount of complex data. This paper reviews the technologies and applications of geospatial information visualization. Finally, the problems and challenges of geospatial visualization are expounded, and the possible future directions are discussed. © 2018 IEEE.

关键词： data visualization

来源：评论

学校读者我要写书评

暂无评论

Android Malware Family Classification and Characterization Using CFG and DFG

Android Malware Family Classification and Characterization U...

引用

Theoretical Aspects of software engineering (TASE)

作者： Zhiwu XU Kerong Ren Fu Song College of Computer Science and Software Engineering Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China School of Information Science and Technology ShanghaiTech University Shanghai China

Android malware has become a serious threat for our daily life, and thus there is a pressing need to effectively mitigate or defend against them. Recently, many approaches and tools to analyze Android malware have been proposed to protect legitimate users from the threat. However, most approaches focus on malware detection, while only a few of them consider malware classification or malware characterization. In this paper, we propose an extension of CDGDroid to classifying and characterizing Android malware families automatically. We first perform static analysis used in CDGDroid to extract control-flow graphs and data-flow graphs on the instruction level. Then we encode the graphs into matrices, and use them to build the family classification models via deep learning. For family characterization, we extract the n-gram sequences from the graphs, which are filtered according to the weights of the classification model built for the target family. And then we construct a vector space model and select the top-k sequences as a characterization of the target family. We have conducted some experiments to evaluate our approach and have identified that the family classification model taking the horizontal combination of CFG and DFG as features offers the best performance in terms of accuracy among all the models. Compared with CDGDroid, Drebin and many antivirus tools gathered in VirusTotal, our family classification model gives a better performance. Finally, We have also conducted experiments on family characterization, and the experimental results have shown that our characterization can capture the malicious behaviors of the testing families.

关键词： Malware Static analysis Tools Task analysis Deep learning Testing software engineering

来源：评论

学校读者我要写书评

暂无评论

Recommending more suitable music based on users’ real context 14th

Recommending more suitable music based on users’ real conte...

引用

14th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2018

作者： Yang, Qing Zhan, Le Han, Li Zhang, Jingwei Bi, Zhongqin School of Electronic Engineering and Automation Guilin University of Electronic Technology Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin541004 China College of Computer Science and Technology Shanghai University of Electronic Power Shanghai200090 China

ISBN: (纸本)9783030129804

Music recommendation is an popular function for personalized services and smart applications since it focuses on discovering users’ leisure preference. The traditional music recommendation strategy captured users’ music preference by analyzing their historical behaviors to conduct personalized recommendation. However, users’ current states, such as in busy working or in a leisure travel, etc., have an important influence on their music enjoyment. Usually, those existing methods only focus on pushing their favorite music to users, which may be not the most suitable for current scenarios. Users’ current states should be taken into account to make more perfect music recommendation. Considering the above problem, this paper proposes a music recommendation method by considering both users’ current states and their historical behaviors. First, a feature selection process based on ReliefF method is applied to discover the optimal features for the following recommendation. Second, we construct different feature groups according to the feature weights and introduce Naive Bayes model and Adaboost algorithm to train these feature groups, which will output a base classifier for each feature group. Finally, a majority voting strategy decides the optimal music type and each user will be recommended more suitable music based on their current context. The experiments on the real datasets show the effectiveness of the proposed method. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Adaptive boosting

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：