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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Qu, Lingxiao Pei, Yan Li, Jianqiang Graduate School of Computer Science and Engineering University of Aizu Fukushima Aizuwakamatsu965-8580 Japan Beijing University of Technology Faculty of Information Technology Beijing100124 China

ISBN: (纸本)9798350337020

We propose a data analysis method that combines the objectives of nonlinear principal component analysis and nonlinear discriminant analysis with the kernel method in a reproducing kernel Hilbert space. This method addresses nonlinear data analysis problems in high-dimensional spaces, specifically the reproducing kernel Hilbert space, through the use of the kernel trick. Our proposed method can be considered as a semi-supervised data analysis approach. We evaluate our proposed method using various kernel functions and datasets, both visually and quantitatively. The evaluation results demonstrate that our proposal outperforms kernel principal component analysis and generalized discriminant analysis in terms of classification performance. This indicates the advantages and originality of our proposed method. Furthermore, we analyze and discuss our findings based on the evaluation results, and highlight potential areas for further research and future work related to our proposal. © 2023 IEEE.

关键词： data analysis method data Science Kernel method Linear Discriminant analysis Principal Component analysis

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Design a Personalized Brain-Computer Interface of LegoRobot Assisted by data analysis method 24

Design a Personalized Brain-Computer Interface of LegoRobot ...

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24th ISPE Inc. International Conference on Transdisciplinary Engineering

作者： Lin, Wan-Jun Chiu, Ming-Chuan Natl Tsing Hua Univ Hsinchu Taiwan

ISBN: (纸本)9781614997795;9781614997788

In our daily life, the data is ubiquitous. With the advent of the data age, people's lives are closely related to it. Therefore, it is important to use these data for analysis to get effective conclusions. Through the data analysis method, we can analyze the results to do effective decisions-making and applications, more applicable to the interface design. Brain-computer interface (BCI) provides the communicated interface between brain and machines such as computers. It's a technique that the users allowed to interact directly with the machine by using brainwave. The technology includes brainwave (EEG) acquisition, feature extraction and translation algorithm. The researches of BCIs since the 1970s began, the most successful case was Jacques Vidal used brainwave signals to stimulate the visual response and controlled the cursor to take the maze of BCI. Nowadays, it has begun to use in medical aids, and improve the inconvenient situation in daily life. However, the applications in "personalized" BCIs are not popular in our life and less of a data validation to support the user-centric design process to provide. Therefore, this study firstly took the mobile application program of the Lego robot designed by the function as an example. Then used the data of the initial test which was assisted by the data analysis method (DAM). The decision made by DAM was to redesign a data-oriented demonstration and user-centered design process (DAUCD). The Lego robot was integrated hardware and software to develop the learnable and personalized BCI. For usability test, we applied the Lego robots to demonstrate the redesign prototype to conduct the usability test. This study not only designed a personalized BCI but also developed a new data-oriented UCD design process. The brand-new method with DAUCD improved the original design and enhanced the usability test. We expect that this personalized BCI will be applied in medical treatments, businesses and livelihood, promoting the welfare o

关键词： Brain-Computer Interface data analysis method User-Centered Design method data analysis User-Centered Design method Usability Testing Personalization Mobile Application

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Automated method for Cosmic Ray data analysis and Detection of Sporadic Effects

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COMPUTATIONAL MATHEMATICS AND MATHEMATICAL PHYSICS 2021年第7期61卷 1129-1139页

作者： Geppener, V. V. Mandrikova, B. S. St Petersburg Electrotech Univ LETI St Petersburg 197022 Russia Russian Acad Sci Inst Cosmophys Res & Radio Wave Propagat Far Eastern Branch Paratunka 684034 Kamchatka Regio Russia

An automated method for detecting multiscale sporadic effects in data from ground-based neutron monitors is proposed. The method is based on the wavelet transform and neural networks of learning vector quantization type (LVQ neural networks). The choice of Daubechies wavelets and Coiflets at the data preprocessing stage is justified. An algorithm for choosing the "best" approximating wavelet basis in the class of orthogonal functions is proposed. The effectiveness of the method as applied to the detection of small-scale sporadic effects is shown experimentally. The possibility of a numerical implementation of the method for operational use is demonstrated.

关键词： data analysis method LVQ neural networks wavelet transform cosmic rays sporadic effects

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method for cosmic ray variation analysis based on the data from global network of neutron monitors 6

Method for cosmic ray variation analysis based on the data f...

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6th International Conference on Information Technology and Nanotechnology (IEEE ITNT)

作者： Geppener, Vladimir Mandrikova, Bogdana St Petersburg Electrotech Univ LETI St Petersurg Russia Inst Cosmophys Res & Radio Wave Propagat FEB RAS Paratunka Kamchatksiy Kra Russia

ISBN: (纸本)9781728170411

An automated method for cosmic ray data analysis and detection of sporadic effect occurrence periods is described. The method is based on joint application of wavelet transform and neural networks of vector quantization. The paper illustrates the results of application of the method during increased solar activity and magnetic storms. The efficiency of the method for detection of sporadic effects, preceding strong magnetic storms, was experimentally confirmed. It was shown that the method can be applied in on-line mode.

关键词： data analysis method neural networks LVQ wavelet transform cosmic rays sporadic effect

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Human Comfort in Indoor Environment: A Review on Assessment Criteria, data Collection and data analysis methods

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IEEE ACCESS 2019年 7卷 119774-119786页

作者： Song, Ting Mao, Fubing Liu, Qing Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Nanyang Technol Univ Sch Comp Sci & Engn Singapore 639798 Singapore Delta Elect Intl Singapore Pte Ltd Singapore 417939 Singapore

Occupants' comfort perception about the indoor environment is closely linked to their health, wellbeing and productivity. Improvement of comfort level in office buildings has significant positive impacts on both employers and employees. Human comfort in indoor environment usually can be assessed in four aspects: thermal comfort, visual comfort, acoustic comfort and respiratory comfort. In this paper, we present a literature review on the previous research contributions towards studying various aspects of human comfort with a special focus on the respective assessment criteria, data collection methods and data analysis approaches employed by former studies. Previous review work has covered the fundamental concepts associated with human comfort. However, their studies mainly focus on thermal comfort and there is limited work that covers other aspects of comfort. Moreover, few of them discuss how the data is obtained, how to extract useful information from the data and how the data is analyzed. To fill up this gap, this paper conducts the survey from the data-driven point of view. Through the survey, we find that sensor technology has been widely used in the data collection for various types of comfort, while so far the machine learning approaches are mainly applied in the area of thermal comfort study. Finally, some potential future research areas are proposed based on the current status of the research work. The established knowledge in this paper would provide useful insights for engineers or researchers who embark on their research in this area.

关键词： Human comfort thermal comfort assessment criteria data analysis method sensor technology machine learning

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Research on method of Fixed Load Aerodynamic Center in the Flight Test for Civil Aircraft 5

Research on Method of Fixed Load Aerodynamic Center in the F...

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5th International Symposium on Computer Science and Intelligent Controls (ISCSIC)

作者： Qiu, Zhijie Wang, Xueliang Commercial Aircraft Corp China Ltd COMAC Flight Test Ctr Shanghai Peoples R China

ISBN: (纸本)9781665416276

AC 25-7c requires the fly-by-wire aircraft to use the HQRM method to evaluate its flight quality under the degraded mode control law. In the flight test stage, the longitudinal static stability needs to be evaluated to get the position of the fixed load aerodynamic center, so as to determine the afterward limit of center of gravity. In this paper, the flight test contents and methods are designed according to the principle of aerodynamic center. Then the data analysis, risk analysis, error analysis and the control of weight and center of gravity carried out.

关键词： aerodynamic center flight test data analysis method error analysis risk analysis

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A New method of Mix Proportion Design of Ordinary Concrete - data analysis method

A New Method of Mix Proportion Design of Ordinary Concrete -...

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2nd International Conference on Civil Engineering, Architecture and Building Materials (CEABM 2012)

作者： Zhou, Wangliang Wuhan Univ Coll Water Resources & Hydroelect Engn Wuhan 430072 Peoples R China

ISBN: (纸本)9783037854235

In the paper, through analyzing large quantity of concrete mix proportions, a law existing in all concrete with different mix proportions and good workability is found, i.e., the volume ratios of sands to binder linearly increase with the increase of the volume ratios of water to binder. Meantime a table of the mass ratios of sands to sands and gravels is given based on numerous concrete mix proportions. According to the table and the linear equation between the volume ratios of sands to binder and the volume ratios of water to binder, a new method of mix proportion design of ordinary concrete - data analysis method is proposed.

关键词： mix proportion design of ordinary concrete data analysis method the volume ratio of sand to binder the volume ratio of water to binder the mass ratio of sand to sand and gravel

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Comparison of prechilling stratification and sulfuric acid scarification on seed germination of Panicum virgatum under drought stress

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Frontiers of Agricultural Science and Engineering 2017年第2期4卷 220-227页

作者： Nan WANG Jing GAO Suiqi ZHANG Feng YAN Shaanxi Collaborative Innovation Center of Chinese Medicinal Resources Industrialization Shaanxi University of Chinese Medicine Institute of Soil and Water Conservation Northwest A&F University College of Pharmacy Shaanxi University of Chinese Medicine

In semi-arid regions of the Loess Plateau,water deficiency restricts plant performance. Panicum virgatum(switchgrass), which is a highly versatile grass,had been introduced to the Plateau as a restoration *** determine if prechilling stratification(PCS) and sulfuric acid scarification(SAS) can optimize establishment,P. virgatum cvs Pathfinder, Trailblazer and Alamo were tested under different ambient water potentials by measuring germination and root and shoot growth along water potential gradients under laboratory conditions. Both PCS and SAS improved total germination percentage(TGP), with PCS being more beneficial. The effect of PCS and SAS on mean germination time(MGT) weakened gradually with increasing drought stress. Both PCS and SAS showed no obvious effect on promoting root and shoot growth. Both PCS and SAS reduced base water potential requirement for reaching 50% germination of Pathfinder and Trailblazer, with this effect greater for *** results indicate that embryo dormancy may be a major factor limiting germination of P. virgatum under drought conditions. Pathfinder appears to be more suitable for a semi-arid environment, whereas Alamo appears to be unsuitable for drought conditions. Given the large difference between predicted value and measured value,the reliability and applicable scope of linear regression estimated ψ_(50) needs further investigation, specification and optimization.

关键词： base water potential data analysis method embryo growth germination

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A data analysis method for detecting wall thermal resistance considering wind velocity in situ

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ENERGY AND BUILDINGS 2010年第10期42卷 1647-1653页

作者： Wang, Fenghao Wang, Dongyang Wang, Xinke Yao, Jianbo Xi An Jiao Tong Univ Sch Human Settlement & Civil Engn Xian 710049 Peoples R China China Nucl Power Engn Co Ltd Zhengzhou Branch Zhengzhou 450052 Peoples R China

To improve the accuracy of data analysis methods for the field measurement of wall thermal resistance, a method considering wind velocity is presented through an analysis of both surface heat flux and temperature samples. This analysis method takes the wall heat transfer of linear system into account, simplifying the first order differential equation of wall transient response based on the nodes of the interior and exterior wall surfaces. An approximate solution has been proposed in the form of time domain interpolation. By applying the weighted residual method for the approximate solution, the data analysis method about temperature, heat flux, and wind velocity can be achieved. A transient heat transfer model of a wall was established applying the infinite difference method, by which the proposed analysis method was validated in this paper. Additionally, the heat flow meter experiment platform considering wind velocity was built, on which the proposed method, the mean method and the dynamic analysis method suggested by the international standard ISO 9869 were applied to the test wall under different wind velocities. The wall thermal resistance value obtained in our proposed method has proven to be in better agreement with that obtained for a steady state. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Wall thermal resistance In-situ measurement data analysis method Wind velocity

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Monitoring changes in behaviour from multi-sensor systems

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HEALTHCARE TECHNOLOGY LETTERS 2014年第4期1卷 92-97页

作者： Amor, James D. James, Christopher J. Univ Warwick Sch Engn Warwick Engn Biomed Coventry CV4 7AL W Midlands England

Behavioural patterns are important indicators of health status in a number of conditions and changes in behaviour can often indicate a change in health status. Currently, limited behaviour monitoring is carried out using paper-based assessment techniques. As technology becomes more prevalent and low-cost, there is an increasing movement towards automated behaviour-monitoring systems. These systems typically make use of a multi-sensor environment to gather data. Large data volumes are produced in this way, which poses a significant problem in terms of extracting useful indicators. Presented is a novel method for detecting behavioural patterns and calculating a metric for quantifying behavioural change in multi-sensor environments. The data analysis method is shown and an experimental validation of the method is presented which shows that it is possible to detect the difference between weekdays and weekend days. Two participants are analysed, with different sensor configurations and test environments and in both cases, the results show that the behavioural change metric for weekdays and weekend days is significantly different at 95% confidence level, using the methods presented.

关键词： automated behaviour-monitoring systems behavioural patterns behavioural sciences computing data analysis method health status medical signal processing multisensor systems patient monitoring sensor fusion

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