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2014 International Conference on Electronic engineering and Information Science, ICEEIS 2014

作者： Wang, Li Jie Zhou, Zhen Qin, Yong Yin, Jin Ying Guo, Jian Ying Dong, Wen Ning Wang, Dan College of measure-control technology and communication engineering Harbin university of science and technology China The higher educational key laboratory on measuring Control technology and instrumentations of Heilongjiang province China

ISBN: (纸本)9783038351467

There are advantages such as real time, quick, multi-constituents simultaneous measurement, green and no pollution, and so on, of using near infrared spectral method to detect concentration information of dairy products constituents. From time domain and frequency domain, near infrared spectral data mining methods based on orthogonality were separately researched to realize noise filtering and useful information extracting. For milk spectrum, methods in the time domain including Orthogonal Signal Correction and Direct Orthogonalization, Wavelet Transform de-noising method in the frequency domain, were separately explored and used in spectral preprocessing, PLS method was used to build calibration model, and processing effect of different data mining methods was compared with and analyzed. It is showed that in the time domain, using the orthogonality methods to make data mining for milk spectrum, the complex interfering signal and noise information uncorrelated with the measured constituents can be can reduced effectively, and the correlated information with the measured constituents is reserved in maximal limitation, prediction capability of calibration model is improved, furthermore, the Orthogonal Signal Correction method is better than the Direct Orthogonalization method, moreover, in the frequency domain, wavelet de-noising is better than the orthogonality methods within the time domain. © (2014) Trans Tech Publications, Switzerland.

关键词： Spectrum analysis

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Magnetite processing and magnetic field analysis of iron ore core inductor in iron grade sensor

Magnetite processing and magnetic field analysis of iron ore...

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2014 International Conference on Manufacturing technology and Electronics Applications, ICMTEA 2014

作者： Wang, Li Jie Li, Jian Xin Sun, Lian Kui Zhang, Fu Jun Yang, Xiu Kun College of Measure-Control Technology and Communication Engineering Harbin University of Science and Technology China The Higher Educational Key Laboratory on Measuring and Control Technology and Instrumentations of Heilongjiang Province China

ISBN: (纸本)9783038353287

In order to realize the online monitoring for iron grade of the magnetite during the dressing process, an iron grade fast measurement method based on electromagnetic induction is given, critical segment of the method is to make the iron grade information acquisition by adopting an iron ore core inductance sensor. Magnetic field analysis for iron ore core inductors of the sensor is explored in the paper. Taking a magnetite in certain regions of Liaoning as the test typical sample examples, physicochemical properties of its raw ore are analyzed, the iron ore samples are prepared and made, and the dressing process are completed. Ferromagnetics features of the magnetite samples above is analyzed, magnetic field distribution of the iron ore core inductor is analyzed, and analytic calculation formula of the magnetic fields is derived. Theory of solving the inductance of iron ore core inductor adopting finite element method of energy is discussed. Furthermore, total finite element design for the iron ore core inductor is made;distribution of electromagnetic field is analyzed. Influence regulations of self-inductance coefficients of the inductor are obtained, thus, the optimal combination of structural parameters of the inductor are designed. There is important practical significance to realize the iron grade testing automation for magnetite and other iron ores of the thesis research above. © (2014) Trans Tech Publications, Switzerland.

关键词： Finite element method

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Machine intelligent diagnosis of ECG for arrhythmia classification using DWT, ICA and SVM techniques

Machine intelligent diagnosis of ECG for arrhythmia classifi...

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IEEE India Conference (INDICON)

作者： Usha Desai Roshan Joy Martis C. Gurudas Nayak Sarika K. G. Seshikala Dept. of Electronics and Communication Engineering NMAM Institute of Technology Nitte Udupi India Dept. of Electronics and Communication Engineering St. Joseph Engineering College Mangaluru India Dept. of Instrumentation and Control Engineering MIT Manipal University Manipal India School of Electronics and Communication Engineering Reva University Bengaluru India

Electrocardiogram (ECG) remains the most reliable and low-cost diagnostic tool to evaluate the patients with cardiac arrhythmias. Manual diagnosis of arrhythmia beats is very tedious due to the nonlinear and complex nature of ECG. Likewise, minute variations in time-domain features viz. amplitude, segments and intervals are difficult to interpret by naked eye. The current paper, describes a machine learning-based approach for computer-assisted detection of five classes of ECG arrhythmia beats using Discrete Wavelet Transform (DWT) features. Further, methodology comprises dimensionality reduction using Independent Component Analysis (ICA), ten-fold cross-validation and classification using Support Vector Machine (SVM) kernel functions. Using ANOVA significant features are selected and reliability of accuracy is measured by Cohen's kappa statistic. Large dataset of 110,093 heartbeats from 48 records of MIT-BIH arrhythmia database recommended by ANSI/AAMI EC57:1998, which are grouped into five classes of arrhythmia beats viz. Non-ectopic (N), Supraventricular ectopic (S), Ventricular ectopic (V), Fusion (F) and Unknown (U) are classified with class specific accuracy of 99.57%, 97.91%, 92.18%, 76.54% and 97.22% respectively and an overall average accuracy of 98.49%, using SVM quadratic kernel. The developed methodology is an efficient tool, which has intensive applications in early diagnosis and mass screening of cardiac health.

关键词： Electrocardiography Support vector machines Discrete wavelet transforms Kernel Feature extraction Diseases Analysis of variance

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Application of neaural network for prediction the cancer patients surviaval status from clinical records

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Journal of Computational Information Systems 2014年第17期10卷 7425-7433页

作者： Wan, Min Fang, Liying Cheng, Wenshuai Wang, Wanjing Zhang, Qixun School of Electronic Information and Control Engineering Beijing University of Technology Beijing China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

In the study of rules in pathological changes, most of analysis view from static perspective, and regard cross-sectional data as input data set to analyze the effect of non-time-varying factors. However, according to the clinical experiences, the changes of physical state can partly reflect the disease progression and the death. Thus, based on the dynamic perspective, the changing patterns of symptom are considered as the model input, longitudinal data is utilized to further explore the rules in pathological changes. This study first proposed a data mining algorithm to find the correlation between patient's symptoms and death, which utilizes the Traditional Chinese Medicine (TCM) and the western medicine clinical records. Furthermore, the prediction of patient's cancer deterioration and death is achieved by using the multi-layer feed forward neural network (MFNN) model, where key symptoms are used as inputs and cancer deterioration and death conditions are used as outputs. The correctness and effectiveness of proposed k-NN and MFNN algorithms are verified by simulation results. The accuracy of data prediction using these data mining algorithms achieves about 94.66%. The experiment indicated that the proposed correlation association analysis and data prediction and pattern matching methods are feasible and effective. Meanwhile, the k-NN model is effective on predicting the next stage of key symptoms and finding out the most probability of patient's cancer deterioration and death for III stage non-small cell lung cancer patients, which is helpful to enhance the accuracy and efficiency of doctor's clinical diagnosis in practice.

关键词： Data mining

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A quick detection approach of magnetic iron grade for magnetite

A quick detection approach of magnetic iron grade for magnet...

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2014 International Conference on Energy Research and Power engineering, ERPE 2014

作者： Wang, He Nan Wang, Li Jie Wang, He Bing Men, Guan Hua Liu, Ye Liu, Hong Yan College of measure-control technology and communication engineering Harbin university of science and technology China Higher educational key lab. on measuring and control tech. and instrumentations of Heilongjiang China

ISBN: (纸本)9783038351603

In order to achieve aims of rapid real-time monitoring iron grade during sales process or mineral processing for the iron ores, a quick detection approach to magnetic iron grade of magnetite based on electromagnetic induction is explored in the paper. Information acquisition head is focused on an iron grade sensor, and the iron grade sensor is made up of coil-windings with magnetite core. Information acquisition circuits are given adapting mode of the transformer bridge type rectifier, and construction of the head is designed and machined. Testing mechanism is analyzed from the angle of magnetic field analysis, and the magnetic field model is also built up. Furthermore, magnetic iron grade of some testing samples are measured by the detection device above. It is showed that when the grade range of the magnetic iron of magnetite is varied from 20% to 65.3%, deviation is lower than 1.0%. By research above, it is shown that the detection method of iron grade based on electromagnetic induction is feasible, and it is also significant for improving the total testing level of mineral processing fields. © (2014) Trans Tech Publications, Switzerland.

关键词： Magnetite

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Research on data interaction of stage visual-effect equipment control system

Research on data interaction of stage visual-effect equipmen...

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International Conference on Electronics Information and Emergency communication

作者： Yujian Jiang Zhonghao Hu Wei Jiang Yingwei Zhang Information Engineering School Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture Beijing Key Laboratory of Modern Entertainment Technology Beijing China

With continuous development of the visual presentation technology on stage, special effect devices have occupied an important place already. In contrast to traditional mutually independent control method, we propose and realize, in this paper, an integrated-control system of stage effect devices. This system ultimately achieve the effect of unified and cooperative control. In addition, we also further discuss work flows and data flows of this system's software console.

关键词： Software Performance evaluation Monitoring Universal Serial Bus Visualization Hardware Presses

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Model Checking of Software Development in Distributed Animation Rendering System

Model Checking of Software Development in Distributed Animat...

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2015 4th National Conference on Electrical,Electronics and Computer engineering(NCEECE 2015)

作者： Zhiguo Hong Yongbin Wang Minyong Shi School of Computer Faculty of Science and EngineeringCommunication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture Beijing Key Laboratory of Modern Entertainment Technology

ISBN: (纸本)9781510819085

Distributed animation rendering systems are used to speed up of rendering i.e the computational-intensive phase of producing animation. How to develop softwares with high availability and efficiency is a hot topic in distributed animation rendering systems. In this paper, based on model checking method for system modeling, three modules(i.e. rendering management server, rendering nodes and storage system) are modeled and analyzed. Firstly, by analyzing the system's typical infrastructure, messages-driven finite state machines of such three modules are studied. Then, the properties of such three modules are described using CTL(Computational Tree Logic). Furthermore, safety and livenesses are verified with SMV(Symbolic Model Verification). The methodology of this paper offers important theoretical guide to software development.

关键词： model checking animation rendering SMV the state machine

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Towards green for relay in InterPlaNetary Internet based on differential game model

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Science China(Information Sciences) 2014年第4期57卷 65-73页

作者： LIN FuHong LIU Qian ZHOU XianWei XIONG Ke School of Computer and Communication Engineering University of Science and Technology Beijing School of Computer and Information Technology Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University

InterPlaNetary Internet(IPN)plays a very important role in the exploitation of ***,the relays in IPN are suffered from high symbol error,limited storage space,and limited available *** analyze the performance of the relay in IPN,in this article,we build a differential game model,where the controller is transmitting rate,and the goal is to maximize the payoff according to the symbol error rate,the storage space and the available energy in the *** such a design,the green relays can be achieved for IPNs,which could prolong the live of the *** the model is not easy to discuss,we analyze it using the Bellman theorem and then get some formulas on the trace of the optimal transmitting ***,extensive simulation results are presented to demonstrate the performance of our proposed model,which shows that by using our derived optimal transmitting rate trace,the relay’s payoff can be maximized.

关键词： IPN differential game symbol error limited storage space energy efficiency

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Set-membership filtering approach for fault detection of systems with unknown-but-bounded noises

Set-membership filtering approach for fault detection of sys...

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Australian control Conference (AUCC)

作者： Yilian Zhang Quanwei Qiu Fuwen Yang Qing-Long Han Ljubo Vlacic Junwei Lu Key Laboratory of Marine Technology and Control Engineering of China Communication Ministry Shanghai Maritime University Shanghai P. R. China School of Information Science and Engineering East China University of Science and Technology Shanghai China Griffith School of Engineering Griffith University QLD Australia

In this paper, a fault detection problem is considered for a class of systems with unknown-but-bounded noises by a set-membership filtering approach. The measurement and the process noises are both considered as unknown-but-bounded. Two ellipsoidal sets, which are one-step-ahead prediction ellipsoid and estimation ellipsoid, are proposed for the state estimation. The fault signal is detected by intersecting the two ellipsoids to check whether the intersection set is empty or not. Recursive algorithms for calculating the two ellipsoids and for detecting whether the fault occurs in the system are developed. Simulation results are provided to illustrate the effectiveness of the proposed method.

关键词： Ellipsoids Fault detection Estimation Noise measurement Mathematical model Australia Prediction algorithms

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