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Structural Performance Analysis of Wall Climbing Robot

IOP Conference Series: Materials Science and Engineering 2019年第4期569卷

作者： Li Huang Shangchun Liao College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan 430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan 430081 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Hubei Wuhan 430081 China

With the development of artificial intelligence technology, robotics technology has become more and more mature. Ground walking robots not only develop rapidly, but also have been applied in actual production and life. However, the development of wall climbing robot technology is still in the laboratory research and small-scale application. We live in a world where progress is continuing. Large-scale buildings, bridges and ships are becoming more and more common. In these places, it is inevitable to involve the construction, maintenance and clarity of high-rise buildings and ships. In the case of dangerous and inefficient manpower work, the application of wall climbing robots can play a very good role. Therefore, the development of wall climbing robots is of vital importance both now and in the future. Starting from the performance characteristics of wall climbing robot, this paper studies and summarizes the moving mode, control mode, conditions to be satisfied and various adsorption forms of wall climbing robot, and introduces the basic research situation in the field of wall climbing robot.

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FPGA Optimal Implementation of PRINCE against Power Analysis Attacks

FPGA Optimal Implementation of PRINCE against Power Analysis...

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ISCC 2017-the 5th International Conference on information Science and Cloud Computing

作者： Yi Zou Lang Li College of Computer Science and Technology Hengyang Normal University Hunan Provincial Key Laboratory of Intelligent Information Processing and Application College of Computer Science and Technology Hengyang Normal University

The algorithm PRINCE proposed in ASIACRYPT 2012 is a lightweight cipher, currently suitable for the implementation on RFID Smart Card of the Io T. It's studied to achieve the optimal implementation of PRINCE encryption algorithm, and to add a fixed random mask to enhance the anti power attacking ability of PRINCE. In this paper, we constructed the same operations into a module called Prince Round, and used counter to control the Prince Round module, while the same round operation runs repeatedly. As a result, it can save registers and effectively reduce the amount of computation. Furthermore, we used a special method by adding the random mask to S-box. The experimental results show that the optimized PRINCE occupies area 9.8% fewer than original PRINCE on FPGA and the encryption with a fixed random mask can run correctly. Last but not least, our research is the first one about the implementation of PRINCE algorithm on FPGA, and can serve as a reference for further application of IOT encryption.

关键词： Matrix FPGA Optimal Implementation of PRINCE against Power Analysis Attacks

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Inferring microRNA-disease association by hybrid recommendation algorithm and unbalanced bi-random walk on heterogeneous network

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Scientific reports 2019年第1期9卷 2474页

作者： Dong-Ling Yu Yuan-Lin Ma Zu-Guo Yu Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education and Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan 411105 P.R. China. Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education and Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan 411105 P.R. China. yuzuguo@***. School of Electrical Engineering and Computer Science Queensland University of Technology Brisbane Q4001 Australia. yuzuguo@***.

More and more research works have indicated that microRNAs (miRNAs) play indispensable roles in exploring the pathogenesis of diseases. Detecting miRNA-disease associations by experimental techniques in biology is expensive and time-consuming. Hence, it is important to propose reliable and accurate computational methods to exploring potential miRNAs related diseases. In our work, we develop a novel method (BRWHNHA) to uncover potential miRNAs associated with diseases based on hybrid recommendation algorithm and unbalanced bi-random walk. We first integrate the Gaussian interaction profile kernel similarity into the miRNA functional similarity network and the disease semantic similarity network. Then we calculate the transition probability matrix of bipartite network by using hybrid recommendation algorithm. Finally, we adopt unbalanced bi-random walk on the heterogeneous network to infer undiscovered miRNA-disease relationships. We tested BRWHNHA on 22 diseases based on five-fold cross-validation and achieves reliable performance with average AUC of 0.857, which an area under the ROC curve ranging from 0.807 to 0.924. As a result, BRWHNHA significantly improves the performance of inferring potential miRNA-disease association compared with previous methods. Moreover, the case studies on lung neoplasms and prostate neoplasms also illustrate that BRWHNHA is superior to previous prediction methods and is more advantageous in exploring potential miRNAs related diseases. All source codes can be downloaded from https://***/myl446/BRWHNHA .

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Superpixel level incremental visual saliency detection in low contrast video 2017

Superpixel level incremental visual saliency detection in lo...

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9th International Conference on Machine Learning and Computing, ICMLC 2017

作者： Zhang, Zhen Xu, Xin Fu, Xiaowei School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial Systems Wuhan University of Science and Technology Wuhan Hubei430065 China

ISBN: (纸本)9781450348171

The last few decades have witnessed the rapid development of saliency detection, which can automatically extract object-of-interest from clutter scene. However, visual saliency detection in low contrast video stream still remains a challenge. In this paper, we present a saliency detection model to detect salient object in low contrast video, which combines spatial saliency computation with temporal saliency computation. In spatial domain, superpixel segmentation and boundary prior are utilized to detect salient object in single video frame. And incremental learning algorithm is employed in temporal domain to effectively update the background model. Extensive experiments demonstrate that this method can achieve better performance. © 2017 ACM.

关键词： Superpixels

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Model-Driven Approach to Hadoop Deployment in Cloud

Model-Driven Approach to Hadoop Deployment in Cloud

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IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)

作者： Zheyi Chen Tao Xiang Xing Chen Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and Technology (TNLIST) Beijing China College of Mathematics and Computer Science Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing Fuzhou China

Due to the diversification of software and hardware resources in cloud and ever-changing demand for deployment, Hadoop deployment is faced with great challenges in difficulty and complexity. Most of present researches lie in environment configuration and parameter setting of deployment, they do not take into account diversification of infrastructure and scalability issues in cloud. In order to quickly customize, deploy and expand Hadoop services according to the demand, a model-driven approach to Hadoop deployment is proposed in the paper. Firstly, Hadoop demand and deployment models are presented. Secondly, the transformation method from the demand model to the deployment model is proposed. Thirdly, the bidirectional synchronization between Hadoop deployment model and running system is realized based on runtime model.

关键词： Computational modeling Runtime Cloud computing Synchronization Virtual machining

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Distributed API protocol mining 29

Distributed API protocol mining

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29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017

作者： Chen, Deng Zhang, Yanduo Wei, Wei Wang, Rongcun Li, Xiaolin Wang, Shixun Huang, Rubing Hubei Provincial Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China School of Computer Science and Technology China University of Mining and Technology Xuzhou China School of Computer and Information Engineering Henan Normal University Xinxiang China School of Computer Science and Telecommunication Engineering Jiangsu University Zhenjiang China

ISBN: (纸本)1891706411

Dynamic Protocol Mining (DPM) techniques are a promising approach to infer useful API protocols automatically. However, their results are biased to input test cases and the instrumentation overhead discounts their usability in industrial practice. In this paper, we propose a distributed dynamic protocol mining framework NSpecMiner. Our framework is based on a client-server architecture, where the client tracer gathers Program Execution Traces (PETs) and sends them to the server for mining. Mined protocols are saved on the server to provide various kinds of remote services, such as API protocol retrieval and program verification, etc. Compared with local miners, NSpecMiner has many advantages: 1) A large number of diverse PETs are likely to be collected from multiple clients, which is essential for mining accurate and complete API protocols. 2) Instrumentation overhead can be balanced among multiple clients. 3) Via integrating the client tracer into widely used software, we can mine API protocols transparently and automatically without any human effort. To evaluate our technique, we performed a comparison test with a local miner ISpecMiner and NSpecMiner. Preliminary results show that our approach is effective to mine useful API protocols as local miners. While our method is able to gather PETs concurrently from multiple clients and other merits of the distributed technology will further benefit DPM significantly.

关键词： Miners

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Combining event-level and cross-event semantic information for event-oriented relation classification by SCNN 15th

Combining event-level and cross-event semantic information f...

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15th China National Conference on Chinese Computational Linguistics, CCL 2016 and 4th International Symposium on Natural Language processing Based on Naturally Annotated Big Data, NLP-NABD 2016

作者： Ding, Siyuan Hong, Yu Zhu, Shanshan Yao, Jianmin Zhu, Qiaoming Provincial Key Laboratory of Computer Information Processing Technology Soochow University Suzhou China

ISBN: (纸本)9783319476735

Previous researches on event relation classification primarily rely on lexical and syntactic features. In this paper, we use a Shallow Convolutional Neural Network (SCNN) to extract event-level and cross-event semantic features for event relation classification. On the one hand, the shallow structure alleviates the over-fitting problem caused by the lack of diverse relation samples. On the other hand, the utilization and combination of event-level and cross-event semantic information help improve relation classification. The experimental results show that our approach outperforms the state of the art. © Springer International Publishing AG 2016.

关键词： Neural networks

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Cooperative Co-evolutionary Artificial Bee Colony Algorithm Based on Hierarchical Communication Model

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Chinese Journal of Electronics 2016年第3期25卷 570-576页

作者： HU Chunyu LIU Hong ZHANG Peng School of Information Science and Engineering Shandong Normal University Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology

Canonical Artificial bee colony(ABC) algorithm with a single species is insufficient to extend the diversity of solutions and may be trapped into the local optimal solution. This paper proposes a new co-evolutionary ABC algorithm(HABC) based on Hierarchical communication model(HCM). HCM combines advantages of global and local communication pattern. With adjustment strategies on species and groups, HCM can reduce the computational complexity dynamically. Performance tests show that the HABC algorithm exhibit good performance on accuracy, robustness and convergence speed. Compared with ABC and Integrated co-evolution algorithm(IABC),HABC performs better in solving complex multimodal functions.

关键词： Artificial bee colony(ABC) algorithm Multi-species co-evolution Hierarchical communication model(HCM) Dynamical adjustment

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Cross-media analysis and reasoning: advances and directions

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Frontiers of information technology & Electronic Engineering 2017年第1期18卷 44-57页

作者： Yu-xin PENG Wen-wu ZHU Yao ZHAO Chang-sheng XU Qing-ming HUANG Han-qing LU Qing-hua ZHENG Tie-jun HUANG Wen GAO Institute of Computer Science and Technology Peking University Department of Computer Science and Technology Tsinghua University Institute of Information Science Beijing Jiaotong University National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of Sciences Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences Department of Computer Science and Technology Xi'an Jiaotong University School of Electronics Engineering and Computer Science Peking University

Cross-media analysis and reasoning is an active research area in computer science, and a promising direction for artificial intelligence. However, to the best of our knowledge, no existing work has summarized the state-of-the-art methods for cross-media analysis and reasoning or presented advances, challenges, and future directions for the field. To address these issues, we provide an overview as follows：（1） theory and model for cross-media uniform representation; （2） cross-media correlation understanding and deep mining; （3） cross-media knowledge graph construction and learning methodologies; （4） cross-media knowledge evolution and reasoning; （5） cross-media description and generation; （6） cross-media intelligent engines; and （7） cross-media intelligent applications. By presenting approaches, advances, and future directions in cross-media analysis and reasoning, our goal is not only to draw more attention to the state-of-the-art advances in the field, but also to provide technical insights by discussing the challenges and research directions in these areas.

关键词： Cross-media analysis Cross-media reasoning Cross-media applications

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Estimation of local and global superpixel covariance for salient object detection in low contrast images 2017

Estimation of local and global superpixel covariance for sal...

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9th International Conference on Machine Learning and Computing, ICMLC 2017

作者： Mu, Nan Xu, Xin Zhang, Xiaolong School of Computer Science and Technology Wuhan University of Science and Technology Wuhan Hubei430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial Systems Wuhan University of Science and Technology Wuhan Hubei430065 China

ISBN: (纸本)9781450348171

Salient object detection has become a hot topic in computer vision as it can substantially facilitate a wide range of applications. Conventional salient object detection models primarily rely on low-level image features, which may face great difficulties in low lighting scenarios. This paper proposes to estimate the saliency of low contrast images via covariance features. The input image is firstly decomposed into superpixel regions to estimate their covariances. Then, the local and global image saliency can be calculated using the covariance features respectively. Finally, a graph-based diffusion process is performed to refine the saliency maps. Extensive experiments have been conducted to evaluate the performance of the proposed model against eleven state-of-the-art models on five benchmark datasets and a nighttime image dataset. © 2017 ACM.

关键词： Superpixels

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