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 comp...
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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.
Structure-preserved denoising of 3D magnetic resonance imaging (MRI) images is a critical step in medical image analysis. Over the past few years, many algorithms with impressive performances have been proposed. In th...
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Aiming at solving the problem of low accuracy of weak texture region and disparity discontinuous region and sensitivity to illumination caused by existing local stereo matching algorithm, a new stereo matching algorit...
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In this paper, we present our system designed for the video emotion recognition task of the Multimodal Emotion Challenge (MEC 2017). Histogram of Oriented Gradients (HOG), face shape (SHAPE), and geometric (GEO) featu...
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ISBN:
(纸本)9781538653128
In this paper, we present our system designed for the video emotion recognition task of the Multimodal Emotion Challenge (MEC 2017). Histogram of Oriented Gradients (HOG), face shape (SHAPE), and geometric (GEO) features are extracted from the detected face images as hand-crafted video features. A pre-trained VGG-Face model is fine-tuned with the face images and emotion labels from the training set of CHEAVD 2.0, the outputs of the penultimate fully-connected layer (FC6) and the last fully-connected layer (FC7) are adopted as Deep Convolutional Neural Network (DCNN) based features. For each video clip, the hand-crafted features and DCNN based features are input into corresponding hidden Markov models (HMMs, one for each emotion class), respectively, for the initial emotion recognitions. The output logarithm likelihood probabilities from the HMMs are then ranked, and the orders constitute an eight-dimensional feature vector as inputs to a Naive Bayes classifier for decision fusion. Experimental results on the CHEAVD 2.0 database show that the combination of FC6, GEO, SHAPE and HOG features obtains the highest macro average precisions (MAPs) on both the validation set (46.61%) and test set (43.88%), which are 12.51% and 22.18% higher than the baseline results, respectively.
In vision science, cascades of Linear+Nonlinear transforms are very successful in modeling a number of perceptual experiences [1]. However, the conventional literature is usually too focused on only describing the for...
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In vision science, cascades of Linear+Nonlinear transforms are very successful in modeling a number of perceptual experiences [1]. However, the conventional literature is usually too focused on only describing the forward input-output transform. Instead, in this work we present the mathematics of such cascades beyond the forward transform, namely the Jacobian matrices and the inverse. The fundamental reason for this analytical treatment is that it offers useful analytical insight into the psychophysics, the physiology, and the function of the visual system. For instance, we show how the trends of the sensitivity (volume of the discrimination regions) and the adaptation of the receptive fields can be identified in the expression of the Jacobian w.r.t. the stimulus. This matrix also tells us which regions of the stimulus space are encoded more efficiently in multi-information terms. The Jacobian w.r.t. the parameters shows which aspects of the model have bigger impact in the response, and hence their relative relevance. The analytic inverse implies conditions for the response and model parameters to ensure appropriate decoding. From the experimental and applied perspective, (a) the Jacobian w.r.t. the stimulus is necessary in new experimental methods based on the synthesis of visual stimuli with interesting geometrical properties, (b) the Jacobian matrices w.r.t. the parameters are convenient to learn the model from classical experiments or alternative goal optimization, and (c) the inverse is a promising model-based alternative to blind machine-learning methods for neural decoding that do not include meaningful biological information. The theory is checked by building and testing a vision model that actually follows the modular program suggested in [1]. Our illustrative derivable and invertible model consists of a cascade of modules that account for brightness, contrast, energy masking, and wavelet masking. To stress the generality of this modular setting we show exa
Battery consistency is an important factor for battery pack performance. Excellent battery consistency can make battery packs more energy efficient and electric vehicles can have longer mileage and higher safety. Thus...
Battery consistency is an important factor for battery pack performance. Excellent battery consistency can make battery packs more energy efficient and electric vehicles can have longer mileage and higher safety. Thus, in this study a comprehensive intelligent clustering methodology for the design of Li-ion battery pack on the basis of uniformity and equalization criteria of the cell was proposed. Firstly, multiple parameters (capacity, voltage, temperature and resistance) test of single cell performance was performed. Secondly, a clustering method combine with self-organizing map neural network (SOM) was proposed. Furthermore, a validation experiment (pack level) was carried out to verify the accuracy of proposed clustering algorithm. It can be concluded that the battery pack formed from SOM sorting results perform better than the battery pack having random cells combination as well as the pack originally purchased from the manufacturer.
With the application and development of cloud computing technology in various fields, the resource utilization rate of the data center has been improved obviously, and the system based on cloud computing platform has ...
With the application and development of cloud computing technology in various fields, the resource utilization rate of the data center has been improved obviously, and the system based on cloud computing platform has also improved the expansibility and stability. In the traditional way, Red5 cluster resource utilization is low and the system stability is poor. This paper uses cloud computing to efficiently calculate the resource allocation ability, and builds a Red5 server cluster based on OpenStack. Multimedia applications can be published to the Red5 cloud server cluster. The system achieves the flexible construction of computing resources, but also greatly improves the stability of the cluster and service efficiency.
Single image super resolution (SR) aims to estimate high resolution (HR) image from the low resolution (LR) one, and estimating accuracy of HR image gradient is very important for edge directed image SR methods. In th...
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With the rapid development of mobile live business, transcoding HD video is often a challenge for mobile devices due to their limited processing capability and bandwidth-constrained network connection. For live servic...
With the rapid development of mobile live business, transcoding HD video is often a challenge for mobile devices due to their limited processing capability and bandwidth-constrained network connection. For live service providers, it’s wasteful for resources to delay lots of transcoding server because some of them are free to work sometimes. To deal with this issue, this paper proposed an Openstack-based flexible transcoding framework to achieve real-time video adaption for mobile device and make computing resources used efficiently. To this end, we introduced a special method of video stream splitting and VMs resource scheduling based on access pressure prediction,which is forecasted by an AR model.
MGMT promoter methylation and IDH1 mutation in high-grade gliomas (HGG) have proven to be the two important molecular indicators associated with better prognosis. Traditionally, the statuses of MGMT and IDH1 are obtai...
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