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Predicting essential proteins based on gene expression data, subcellular localization and PPI data 1

12th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2017

作者： Lei, Xiujuan Wang, Siguo Pan, Linqiang School of Computer Science Shaanxi Normal University Xi’anShaanxi710119 China Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology WuhanHubei430074 China School of Electric and Information Engineering Zhengzhou University of Light Industry ZhengzhouHenan450002 China

ISBN: (数字)9789811071799

ISBN: (纸本)9789811071782

Predicting essential proteins is indispensable for understanding the minimal requirements of cellular survival and development. In recent years, many methods combined with the topological features of PPI networks have been proposed. However, most of these approaches ignored the intrinsic characteristics of biological attributes. This paper integrates Gene expression data, Subcellular localization and PPI networks to identify essential proteins, named GSP. We use local average connectivity and edge clustering coefficient unite with gene expression data to measure centralities of nodes. Compared with non-essential proteins, essential proteins appear more frequently in some subcellular localizations such as Nucleus and considering that different compartments play different roles, thus we integrate subcellular localization information to identify essential proteins. The computational experiment results on the yeast PPI networks show that the proposed method GSP outperforms other state-of-art methods including DC, EC, IC, SC, NC, LAC, PeC, WDC and UDoNC. © Springer Nature Singapore Pte Ltd 2017.

关键词： Proteins

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Trajectory Planning for 6-DOF Robotic Arm Based on Quintic Polynormial

Trajectory Planning for 6-DOF Robotic Arm Based on Quintic P...

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2017 2nd International Conference on Control, automation and Artificial Intelligence(CAAI2017)

作者： Xiaojie Zhao Maoli Wang Ning Liu Yongwei Tang Shandong Computer Science Center (National Supercomputer Center in Jinan) Shandong Provincial Key Laboratory of Computer Networks School of automation engineering Qufu Normal University

ISBN: (纸本)9781510845541

The paper deals with research on polynomial trajectory planning for 6-DOF robotic arm. On the basis of kinematics analysis, we carried out trajectory planning and simulation of joint space. Through the trajectory planning diagrams of MATLAB simulation on the two methods, the results showed that quintic polynomial is better than cubic polynomial in the effect of planning. As a result, this method used in six degrees of freedom industrial robot trajectory planning is feasible.

关键词： robotic arm trajectory planning 6-DOF polynomial

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Understanding the feedforward artificial neural network model from the perspective of network flow

arXiv

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arXiv 2017年

作者： Dai, Dawei Tan, Weimin Zhan, Hong School of Computer Science Shanghai Key Laboratory of Data Science Fudan University Shanghai China School of Automation Science and Engineering South China University of Technology GuangZhou China

In recent years, deep learning based on artificial neural network (ANN) has achieved great success in pattern recognition. However, there is no clear understanding of such neural computational models [1], for instance, for a trained ANN-classifier, we have no idea of why some classes are easy to be predicted correctly, but some are difficult to be predicted correctly. In this paper, we try to unravel ''black-box" structure of classifiers and explain the mechanism of classification decisions made by classifiers from network flow. Specifically, we consider the feed forward artificial neural network as a network flow model, which consists of many directional class-pathways. Each class-pathway encodes one class. The class-pathway of a class is obtained by connecting the activated neural nodes in each layer from input to output, where activation value of neural node (node-value) is defined by the weights of each layer in a trained ANN-classifier. From the perspective of the class-pathway, training an ANN-classifier can be regarded as the formulation process of class-pathways of different classes. By analyzing the the distances of each two class-pathways in a trained ANN-classifiers, we try to answer the questions, why the classifier performs so? The smaller the distance of the class-pathways between two classes is, the higher the probability of the predicted error each other for these two classes will be. Furthermore, we can use the analysis as a new way to measure the performance of classifier and compare them despite their high prediction accuracy reporting on the small test sets. At last, from the neural encodes view, we define the importance of each neural node through the class-pathways, which is helpful to optimize the structure of a classifier. Experiments for two types of ANN model including multi-layer perceptron (MLP) and convolutional neural network (CNN) verify that the network flow based on class-pathway is a reasonable explanation for ANN models. Copyright

关键词： Classification (of information)

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A method for correcting illumination unevenness of solar image 8

A method for correcting illumination unevenness of solar ima...

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8th IEEE International Conference on Software engineering and Service science, ICSESS 2017

作者： Yang, Hongjuan Ji, Kaifan Yang, Yunfei Duan, Wenliang Deng, Hui Liang, Bo Yunnan Key Lab. of Computer Technology Application/Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Yunnan Observatory Chinese Academy of Sciences Kunming Yunnan China Key Laboratory of Solar Activity National Astronomical Observatories Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781538645703

Traditional correction methods can not be used to correct effectively the solar images with uneven illumination, such as the bilinear interpolation method. We adopt an improved algorithm that combine the background fitting method and the mask method. The algorithm consists of the following main steps: segmenting the image, selecting the sampling points, interpolating the sampling points, calculating the mask, correcting the image. By comparing four evaluation indicators of the corrected image, including the information entropy of the image, the mean brightness, the mean variance and the peak signal-to-noise ratio (PSNR), this improved algorithm is proved to be effectively in the solar images with uneven illumination. © 2017 IEEE.

关键词： Interpolation

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Sampled-data H∞ filter for delayed neural network subject to sensor saturation

Sampled-data H∞ filter for delayed neural network subject t...

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第36届中国控制会议

作者： Liuwen Li Wenlin Zou Shumin Fei Jie Cao Pan Wang Key Laboratory of Measurement and Control of CSE (Ministry of Education) School of AutomationSoutheast University School of Information Engineering Nanjing Xiaozhuang University School of Computer Science and Engineering Nanjing University of Science and Technology

This paper is concerned with the problem of sampled-data H∞filtering for delayed neural network subject to sensor saturation. Rather than the continuous measurements, the neural network measurements are sampled and then transmitted to the filter simultaneously considering sensor saturation constraints. By using the input delay approach,the sampling period is converted into a bounded time-vary delay in the filter error system. Sensor saturation function is decomposed into a linear part and a dead-zone nonlinear remainder term. By utilizing Lyapunov-functional approach,sufficient conditions have been obtained to ensure that the filter error dynamics is exponentially stable. Finally, an example is provided to illustrate the superiority and usefulness of the proposed filter approach.

关键词： sampled-data systems sensor saturation H_∞ filter delayed neural network

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Testing automation systems by means of model checking

Testing automation systems by means of model checking

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Igor Buzhinsky Valeriy Vyatkin Computer Technologies Laboratory ITMO University St. Petersburg Russia Department of Electrical Engineering and Automation Aalto University Finland Department of Computer Science Electrical and Space Engineering Luleå University of Technology Sweden

Industrial automation systems are commonly obliged to comply with correctness requirements and safety standards. Testing and simulation are traditionally used to ensure this compliance. For mission-critical applications, formal verification and model checking in particular are also used, but such techniques are computationally intensive and difficult to apply in practice. This paper searches for synergies between testing and model checking by generalizing an earlier proposed formal test modeling framework. It presents a technique of testing automation systems with the use of model checking, which now supports multiple model checking environments and a more generic test case representation. The proposed technique is applied on a case study involving a simple safety-critical system with timing requirements. Experiments show that the technique is fast despite the use of formal methods and at the same time has several benefits compared to usual testing.

关键词： Model checking automation Computational modeling IEC Standards Closed loop systems

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Design of hybrid damping controller based on multi-target gravitational search optimization algorithm in a multi-machine power system with high penetration of PV park

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Journal of Central South University 2016年第5期23卷 1163-1175页

作者： Y.Hashemi H.Shayeghi M.Moradzadeh A.Safari Technical Engineering Department University of Mohaghegh Ardabili Centre of Excellence for Power System Automation and Operation Department of Electrical EngineeringIran University of Science and Technology Centre for Engineering Innovation Department of Electrical and Computer EngineeringUniversity of Windsor Electrical Energy Laboratory Department of Electrical EnergySystems and AutomationGhent University Department of Electrical Engineering Azarbaijan Shahid Madani University

A mathematical approach was proposed to investigate the impact of high penetration of large-scale photovoltaic park(LPP) on small-signal stability of a power network and design of hybrid controller for these units.A systematic procedure was performed to obtain the complete model of a multi-machine power network including *** damping of oscillations focusing on inter-area oscillatory modes,a hybrid controller for LPP was *** performance of the suggested controller was tested using a 16-machine 5-area *** results indicate that the proposed hybrid controller for LPP provides sufficient damping to the low-frequency modes of power system for a wide range of operating *** method presented in this work effectively indentifies the impact of increased PV penetration and its controller on dynamic performance of multi-machine power network containing *** results demonstrate that the model presented can be used in designing of essential controllers for LPP.

关键词： hybrid controller multi-objective optimization large-scale photovoltaic park small-signal scrutiny

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On active decoupling control for horizontal-lateral direction of hypersonic flight based on HIFOO 21

On active decoupling control for horizontal-lateral directio...

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21st AIAA International Space Planes and Hypersonics Technologies Conference, Hypersonics 2017

作者： Ma, Shunjian Zhu, Kai Sun, Mingwei Wang, Zenghui Chen, Zengqiang Dept. of Automation and Intelligent Science Nankai University College of Computer and Control Engineering Tianjin300350 China Beijing Aerospace Technology Institute Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Beijing Aerospace Technology Institute Beijing100074 China Department of Electrical and Mining Engineering University of South Africa FL1710 South Africa

ISBN: (数字)9781624104633

ISBN: (纸本)9781624104633

Nowadays, hypersonic flight vehicles are widely studied. Since their high nonlinearity, strong coupling and uncertain factors, the conventional three-channel independent control design method is often unable to work well. In this paper, an active disturbance rejection controller (ADRC) is utilized to cancel internal uncertainties and exogenous disturbances for longitudinal dynamics. Then, the MIMO robust controller is obtained by choosing proper sensitivity functions and weighting functions to reduce horizontal-lateral direction coupling. The conventional H robust controllor is high-order, which is difficult for practitioners to implement. With frequency transformation, both ADRC for the longitudinal dynamics and MIMO robust controller for the horizontal-lateral dynamics are reformed into the static output feedback structure to reduce the high order of controller. Finally, all parameters in the controllers can be optimized by HIFOO (H-Infinity Fixed Order Optimization). The Winged-Cone, a 6-freedom NASA hypersonic vehicle model, is used as a benchmark, and Monte Carlo simulations demonstrate the effectiveness of the proposed method. © 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Controllers

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3D RoI-aware U-net for accurate and efficient colorectal tumor segmentation

arXiv

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arXiv 2018年

作者： Huang, Yi-Jie Dou, Qi Wang, Zi-Xian Liu, Li-Zhi Jin, Ying Li, Chao-Feng Wang, Lisheng Chen, Hao Xu, Rui-Hua Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University China Imsight Medical Technology Co. Ltd. China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Sun Yat-sen University Cancer Center State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine Guangzhou China

Segmentation of colorectal cancerous regions from 3D Magnetic Resonance (MR) images is a crucial procedure for radiotherapy which conventionally requires accurate delineation of tumour boundaries at an expense of labor, time and reproducibility. While deep learning based methods serve good baselines in 3D image segmentation tasks, small applicable patch size limits effective receptive field and degrades segmentation performance. In addition, Regions of interest (RoIs) localization from large whole volume 3D images serves as a preceding operation that brings about multiple benefits in terms of speed, target completeness, reduction of false positives. Distinct from sliding window or non-joint localization-segmentation based models, we propose a novel multitask framework referred to as 3D RoI-aware U-Net (3D RU-Net), for RoI localization and in-region segmentation where the two tasks share one backbone encoder network. With the region proposals from the encoder, we crop multi-level RoI in-region features from the encoder to form a GPU memory-efficient decoder for detail-preserving segmentation and therefore enlarged applicable volume size and effective receptive field. To effectively train the model, we designed a Dice formulated loss function for the global-to-local multi-task learning procedure. Based on the efficiency gains demonstrated by the proposed method, we went on to ensemble models with different receptive fields to achieve even higher performance costing minor extra computational expensiveness. Extensive experiments were subsequently conducted on 64 cancerous cases with a four-fold cross-validation, and the results showed significant superiority in terms of accuracy and efficiency over conventional state-of-the art frameworks. In conclusion, the proposed method has a huge potential for extension to other 3D object segmentation tasks from medical images due to its inherent generalizability. The code for the proposed method is publicly available. Copyright ©

关键词： Signal encoding

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Yet Another Robot Application?

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IEEE ROBOTICS & automation MAGAZINE 2016年第2期23卷 12-+页

作者： Salvini, Pericle Korsah, Ayorkor Nourbakhsh, Illah Department of Computer Architecture and Automation Computer Science Faculty Complutense University of Madrid c∖José García Santesmases s∖n Madrid Spain Key Laboratory of Dependable Service Computing in the Cyber Physical Society of the Ministry of Education Chongqing University and the College of Automation Chongqing University Chongqing China School of Automation Chongqing University Chongqing China Department of Electrical Engineering and Computer Science Northwestern University Evanston IL School of Electrical and Electronic Engineering Nanyang Technological University Singapore

The articles in this special section is to find out what lies beyond the fascination toward robots that we have inherited from popular culture, the pleasure of learning with robots derived from the gamification of learning, and the strong appeal for robotics technologies given by its aura of innovation. Are there authentic ways in which robotics can improve education, and what affordances does robotics, in particular, provide for such educational transformation? Indeed, one of the biggest gray areas of educational robotics concerns the lack of empirical evidence on the educational (pedagogical as well as psychological) effectiveness of robots that is related to both the lack of standardized evaluation criteria and the methodological difficulties in conducting sound scientific tests.

关键词： Special issues and sections Robots computer applications Technology forecasting engineering education STEM Education Programming

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