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Ordering policies and coordination in a twoechelon supply chain with Nash bargaining fairness concerns

Journal of Management Analytics 2017年第1期4卷 55-79页

作者： Caimin Wei Zhongping Li Zongbao Zou Department of Mathematics Shantou UniversityShantou 515063People’s Republic of China Guangdong Provincial Key Lab of Digital Signals and Image Processing Shantou UniversityShantou 515063People’s Republic of China Sun Yat-Sen Business School Sun Yat-sen UniversityGuangzhou 510275People’s Republic of China

This paper investigates the ordering policies of two competitive retailers,and the coordination status of a two-echelon supply chain by considering the fairness concerns of channel *** consider that two retailers compete with each other over price,where overstock and shortage are *** assume that the demand is stochastic and considered with additive ***,based on the Nash bargaining fairness reference point,we obtain the optimal decisions of the fairness-concerned channel members in both the centralized and the decentralized cases using a two-stage game ***,we analyze the coordination status of the supply chain with Nash bargaining fairness concerns using ideas of ***,numerical experiments are used to illustrate the influence of some parameters,the fairness-concerned behavioral preference of the channel members on the optimal decisions and the coordination status of supply *** managerial insights are obtained.

关键词： supply chain Nash bargaining fairness concern sale price coordination

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Attention Electroencephalogram Analysis based on Jensen-Shannon Divergence Analysis

Attention Electroencephalogram Analysis based on Jensen-Shan...

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2013 International Conference on Bio-Medical Materials and Engineering(ICBME 2013)

作者： Zhengzhong Zheng Junchang Zhao Xiaolin Huang Jun Wang Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm Institute of Biomedical Electronic Engineering School of Electronic Science and EngineeringNanjing University

In this paper, the complexity analysis method based on Jensen-Shannon Divergence was used to calculate the complexity of the Idle states, the close eyes states and the count numbers states electroencephalogram The study found that the JSD value of close eyes states EEG was highest, followed by that of the Idle states EEG, and that of the count numbers states EEG was minimum The result can be used to assisted clinical diagnosis

关键词： Complexity electroencephalogram Jensen-Shannon Divergence

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Beta Wave of Sleep Electroencephalogram Analysis Based on Multiscale Sign Series Entropy

Beta Wave of Sleep Electroencephalogram Analysis Based on Mu...

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2015 International Conference on Artificial Intelligence and Industrial Engineering(AIIE 2015)

作者： Jianhui Jiang Shitong Wang Fengzhen Hou Jun Wang Jin Li Image Processing and Image Communications Key Lab. Nanjing Univ.of Posts & Telecomm School of Science China Pharmaceutical University College of Physics and Information Technology Shaanxi Normal University

ISBN: (纸本)9781510806450

Sleep Electroencephalogram(Sleep EEG) detection and treatment can provide the basis for clinical diagnosis and treatment. According to the non-stationary random character of EEG itself, the paper proposed multiscale sign series entropy(MSSE) method and applied it to the state of sleep EEG analysis. Numerical results showed that, MSSE method can effectively differentiate awake period β wave and sleep stage β wave even if under the influence of the noise. The results show that the algorithm can aid in clinical diagnosis of sleep EEG.

关键词： sleep electroencephalogram multiscale sign series entropy clinical diagnosis

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Beta wave of sleep electroencephalogram analysis based on sign series entropy

Beta wave of sleep electroencephalogram analysis based on si...

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2016 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2016)

作者： Min Zhao Yuting Li Lu Yang Jia-Fei Dai Jun Wang Feng-Zhen Hou Image Processing and Image Communications Key Lab. Nanjing Univ.of Posts & Telecomm. Nanjing General Hospital of Nanjing Military Command School of Science China Pharmaceutical University

ISBN: (纸本)9781510823808

Sleep and wake EEG have some *** studying their brain waves and calculating the sign series entropy,we use the T test for the detection of sleep and wake EEG data to figure out whether they are *** beta waves being filtered out by the filter,we calculate the entropy of the sign *** results of T test show that the beta waves in the state of sleep and wake are different.

关键词： sleep EEG sign series entropy

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Coupling analysis of epileptic EEG signals based on the multiscale mutual model entropy

Coupling analysis of epileptic EEG signals based on the mult...

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2016 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2016)

作者： Ning Ji Jia-Fei Dai Jun Wang Feng-Zhen Hou Image Processing and Image Communications Key Lab. Nanjing Univ.of Posts & Telecomm. Nanjing General Hospital of Nanjing Military Command School of Science China Pharmaceutical University

ISBN: (纸本)9781510823808

The Multiscale Mutual Model Entropy algorithm is presented to quantify the coupling degree between two EEG time series collected at the same time on different *** extracted the characteristics of EEG signals from the healthy and epileptics based on the *** results show that the entropy value of healthy people is higher than that of *** with the increase of scale,the difference in entropy value between them is more *** indicates that Multiscale Mutual Entropy can distinguish the coupling difference between normal samples and case samples,which is significant for the clinical pathological assessment and brain disease diagnosis.

关键词： multiscale epileptic coupling mutual model entropy

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Sleep EEG analysis Based on the Multiscale Jenson-Shannon Divergence

Sleep EEG analysis Based on the Multiscale Jenson-Shannon Di...

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2016 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2016)

作者： Zhengxia Zhang Jia-Fei Dai JunWang Feng-Zhen Hou Image Processing and Image Communications Key Lab. Nanjing Univ.of Posts & Telecomm. Nanjing General Hospital of Nanjing Military Command School of Science China Pharmaceutical University

ISBN: (纸本)9781510823808

Sleep EEG signals analysis is a hotspot of research recently,this paper,by using nonlinear dynamics theory knowledge,JSD algorithm and multi-scale JSD algorithm is proposed for some individual conscious period and NREM sleep stage I analyzed the research of EEG signals,and the use of SPSS statistical software to verify the veracity and reliability of the experiment,at the same time,with the error bar graph method to analysis the two different states of sleep EEG signals,the results show that both the JSD algorithm and the multi-scale JSD algorithm can effectively distinguish between awake and NREM sleep stage I of EEG signals,these two conditions' EEG signals exist significant differences,The algorithm we proposed can be further used in the study of sleep EEG in installment,which can also provide all kinds of disease diagnosis and treatment of sleep with effective auxiliary function,the research has important practical significance in the future.

关键词： multi-scale JSD sleep EEG signals

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Fetal Electrocardiogram Extraction Based On Modified Robust Independent Component Analysis

Fetal Electrocardiogram Extraction Based On Modified Robust ...

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2013 International Conference on Bio-Medical Materials and Engineering(ICBME 2013)

作者： Wenpo Yao Junchang Zhao Zhengzhong Zheng Tiebing Liu Hongxing Liu Jun Wang Image Processing and Image Communications Key Lab. Nanjing Univ. of Posts & Telecomm Nanjing General Hospital of Nanjing Military Command School of Electronic Science and Engineering Nanjing University

Fetal electrocardiogram(FECG) separation gets widely attention due to its clinical significance In the paper, we proposed an improved robust independent component analysis for fetal ECG separation Firstly, wavelet decomposition was applied to fetal ECG to get the relevant parameters Then, the Robust ICA was used to separate the mixed signals Compared to robust independent component analysis, computing speed of the improved algorithm increased by an average of 15 percent while minimum mean square error fluctuations 00008, which indicated that this algorithm could be effectively used in clinical fetal ECG monitoring

关键词： Robust ICA Wavelet Transform FECG Kurtosis

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Alpha Wave Attention EEG Analysis Based on the Multiscale Jensen-Shannon Divergence

Alpha Wave Attention EEG Analysis Based on the Multiscale Je...

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2014 2nd International Conference on Materials Science and Mechanical Engineering(2nd ICMSME 2014)

作者： Zhengxia Zhang Siqiu Xu Erning Zhou Xiaolin Huang Jun Wang Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm Institute of Biomedical Electronic Engineering School of Electronic Science and EngineeringNanjing University

The article adopted the multiscale Jensen- Shannon Divergence method for EEG complexity analysis. Then the study found that the method can distinguish between three different status(eyes closed, count, in a daze) acquisition of Alpha EEG time series, which shows three different states of Alpha EEG time series having significant differences. In each state of the three different states(eyes closed, count, in a daze), we aimed at comparing and analyzing the statistical complexity of EEG time series itself and the statistical complexity of EEG time series proxy data, finding that there are large amounts of nonlinear time series in the Alpha EEG signals. This method is also fully proved that the multiscale JSD algorithm can be used to analyze EEG signals. Attention statistical complexity can be used as a measure of brain function parameter, which can be applied to the auxiliary clinical brain function evaluation in the future.

关键词： Multiscale JSD Attention Alpha EEG signals

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BAF-Net: Bidirectional Attention-aware Fluid Pyramid Feature Integrated Multi-modal Fusion Network for Prognosis

BAF-Net: Bidirectional Attention-aware Fluid Pyramid Feature...

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2022 IEEE Nuclear Science Symposium, Medical Imaging Conference, and Room Temperature Semiconductor Detector Conference, IEEE NSS MIC RTSD 2022

作者： Wu, Huiqin Lv, Wenbing Du, Dongyang Xu, Hui Lin, Guoyu Zhou, Zidong Ma, Jianhua Lu, Lijun Southern Medical University School of Biomedical Engineering Guangdong Guangzhou510515 China Southern Medical University Guangdong Provincial Key Laboratory of Medical Image Processing The Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology Guangzhou510515 China Pazhou Lab Guangzhou510330 China

ISBN: (纸本)9781665488723

In this work, we proposed a bidirectional attention-aware fluid pyramid features integrated fusion network (BAF-Net) with cross-modal interactions for multi-modality medical images prognosis. The network is composed of two identical branches to preserve the unimodal feature and one paralleled bidirectional attention-aware distillation stream to assimilate cross-modal complements progressively and learn supplementary refined features in both the bottom-up and the top-down processes. The fluid pyramid connections were adopted to integrate the hierarchical features at different levels of deep neural network, and channel-wise attention modules were exploited to mitigate the cross-modal cross-level incompatibility. Furthermore, the depth-wise separable convolution was introduced to fuse the cross-modal cross-level features to alleviate the increase of parameters to a great extent. Better performance was obtained by the proposed BAF-Net compared to unimodal network for cancer prognosis in a public TCIA dataset (head & neck cancer (HNC) dataset composed of 800 patients from nine centers). © 2022 IEEE.

关键词： Bidirectional attention-aware deep learning diagnosis and prognosis fluid pyramid feature integration multi-modalities fusion

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Group detection in complex scene by split-merge strategy

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ICIC Express Letters, Part B: Applications 2015年第12期6卷 3219-3224页

作者： Chen, Qiao Chen, Changhong Xie, Xiaofang Liu, Feng Key Lab of Image Processing and Image Communications of Jiangsu Province Nanjing University of Posts and Telecommunications No. 66 New Mofan Road Nanjing210003 China Department of Electrical Engineering Laiwu Vocational and Technical College Laiwu271100 China

Detection of groups of interacting people is a difficult task, especially in an unconstrained and crowded environment. In this paper, as a main contribution, we present a novel and efficient framework for social group detection, which is based on the theories of social distance model and social force model. Besides, we propose a new method to find the relationships between individuals in a scene, which is based on splitmerge strategy. The results demonstrate that our approach obtains effective performance in a more generic scene where many other methods fail. © 2015, ICIC Express Letters Office. All rights reserved.

关键词： Group theory

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